Cuevas-Tello, Juan C., Tino, Peter, Raychaudhury, Somak, Yao, Xin, Harva, Markus
We study the problem of estimating the time delay between two signals representing delayed, irregularly sampled and noisy versions of the same underlying pattern. We propose and demonstrate an...
The Centre of Excellence for Research in Computational Intelligence and Applications (2009)
Abstract. Dynamic time-linkage problems (DTPs) are common types of dynamic optimization problems where "decisions that are made now... may in‡uence the maximum score that can be obtained in...
This paper introduces drift analysis and its applications in estimating average computation time of evolutionary algorithms. Firstly, drift conditions for estimating upper and lower bounds of the...
Evolving Neural Networks for Chlorophyll-a Prediction (2009)
This paper studies the application of evolutionary arti cial neural networks to chlorophyll-a prediction in Lake Kasumigaura. Unlike previous applications of arti cial neural networks in this eld,...
Target Shape Design Optimization by Evolving Splines (2009)
Pan Zhang, Xin Yao, Lei Jia, B. Sendhoff, Senior Member, T. Schnier
Abstract — Target shape design optimization problem (TS-DOP) is a miniature model for real world design optimization problems. It is proposed as a test bed to design and analyze optimization...
Time Complexity of Maximum Matching by an (N + N) Evolutionary Algorithm (2009)
An (N +N) evolutionary algorithm is considered for the problem of finding the maximum cardinality matching in a graph. It is shown that the performance of the evolutionary algorithm is the same as...
1. One approach to drug design is to find molecules similar to good drugs but have fewer negative side effects. 2. Ideally, a candidate replacement drug is sufficiently similar to have the same...
1 A Computational Intelligence Approach To Railway Track Intervention Planning (2008)
Derek Bartram, Michael Burrow, Xin Yao
Summary. Railway track intervention planning is the process of specifying the location and time of required maintenance and renewal activities. To facilitate the process, decision support tools have...
Measuring Generalization Performance in Coevolutionary Learning (2008)
Siang Yew Chong, Peter Tiño, Xin Yao
Coevolutionary learning involves a training process where training samples are instances of solutions that interact strategically to guide the evolutionary (learning) process. One main research issue...
Self-Adapting Payoff Matrices in Repeated Interactions (2008)
Abstract-Traditional iterated prisoner's dilemma (IPD) as- in light of the opponent's, is fixed and symmetric. That is, sumed a fixed payoff matrix for all players, which may not be the...
Xiaoli Li, Dong Cui, Premysl Jiruska, John E Fox, Xin Yao
Abstract: The purpose of the present paper is to develop a method, based on equal-time correlation, correlation matrix analysis and surrogate resampling, which is able to quantify and describe...
Target Shape Design Optimization by Evolving Splines (2008)
Pan Zhang, Xin Yao, Lei Jia, B. Sendhoff, Senior Member, T. Schnier
Abstract — Target shape design optimization problem (TS-DOP) is a miniature model for real world design optimization problems. It is proposed as a test bed to design and analyze optimization...
Traditional Design Process (2008)
Xin Yao, Xin Yao, Xin Yao, Xin Yao
• The design of new molecules based on desired physical, chemical and biological properties. • Industrial applications include designing composites and blends, drugs, agricultural chemicals such...
Abstract: Using a coordinated group of simple solvers to tackle a complex problem is not an entirely new idea. Its root could be traced back hundreds of years ago when ancient Chinese suggested a...
Evolutionary ensemble for in silico prediction of ames test mutagenicity (2008)
Abstract. Driven by new regulations and animal welfare, the need to develop in silico models has increased recently as alternative approaches to safety assessment of chemicals without animal testing....
Neural-Based Learning Classifier Systems (2008)
Hai H. Dam, Hussein A. Abbass, Chris Lokan, Xin Yao, Hai H. Dam, Hussein A. Abbass, ...
UCS is a supervised learning classifier system that was introduced in 2003 for classification in data mining tasks. The representation of a rule in UCS as a univariate classification rule is...
Measuring Generalization Performance in Co-evolutionary Learning (2008)
Siang Y. Chong, Peter Tiño, Xin Yao
Co-evolutionary learning involves a training process where training samples are instances of solutions that interact strategically to guide the evolutionary (learning) process. One main research...
Jin Li, Xiaoli Li, Colin Frayn, Peter Tino, Xin Yao
Applications (CERCIA) is a unique new initiative, aimed to be an international leader in applied research and knowledge transfer of computational intelligence techniques for the benefit of industry...
The Centre of Excellence for Research in Computational Intelligence and Applications (2008)
This paper compares three different evolutionary algorithms for solving the node covering problem: EA-I relies on the definition of the problem only without using any domain knowledge, while EA-II...
SENSITIVITY ANALYSIS IN MULTI-OBJECTIVE EVOLUTIONARY DESIGN (2008)
Meng Hiot Lim, Xin Yao, Lipo Wang (editors, Johan Andersson
In real world engineering design problems we have to search for solutions that simultaneously optimize a wide range of different criteria. Furthermore, the optimal solutions also have to be robust....
Automatic Divide-and-Conquer Using Populations and Ensembles Abstract (2008)
Real-world problems are often too large and complex for a single monolithic system to solve. In practice, the divide-and-conquer strategy has often been used to decompose a large and complex problem...
Efficient Forward Regression with Marginal Likelihood (2008)
Abstract. We propose an efficient forward regression algorithm based on greedy optimization of marginal likelihood. It can be understood as a forward selection procedure which adds a new basis vector...
Abstract. This paper presents an online demo of evolutionary programming using a mixed mutation strategy for solving function optimization problems. The strategy combines three different mutation...
Multi-objective Ensemble Construction, Learning and Evolution (2008)
Abstract. An ensemble of learning machines has been theoretically and empirically shown to generalise better than single learners. Diversity and accuracy are two key properties that ensemble members...
Jun He, Colin Reeves, Carsten Witt, Xin Yao
Various ways have been defined to measure the hardness of a fitness function for evolutionary algorithms and other black-box heuristics. Examples include fitness landscape analyses, epistasis,...
Yong Liu, Tetsuya Higuchi, Xin Yao
Based on negative correlation learning and evolutionary learning, this paper presents evolu-tionary ensembles with negative correlation learning (EENCL) to address the issues of automatic...
To Understand Fitness Landscapes in Continuous Space by Using Drift Analysis (2008)
Abstract — This paper gives an explanation of fitness landscapes in continuous space by using drift analysis. Firstly we first describe the characteristics of easy and hard landscapes, and then...
To Understand One-Dimensional Continuous Fitness Landscapes by Drift Analysis (2008)
Abstract. This paper shows that we could describe the characteristics of easy and hard fitness landscapes in one-dimensional continuous space by drift analysis. The work expends the existing results...
Ensemble Regression Trees for Time Series (2008)
Huanhuan Chen, Student Member, Xin Yao
Abstract — This paper propose to combine Bootstrap sampling and random subspace method for time series forecasting problems. The algorithm and methodology are described for the NN3 forecasting...
Type-I Topological Logic C 1 T and Approximate Reasoning (2008)
Yalin Zheng, Changshui Zhang, Xin Yao
Abstract. We introduce the consistent topological structure and neighborhood structure into the logical framework for providing the logical foundation and logical normalization for the approximate...
Abstract Fast Evolutionary Programming (2008)
Evolutionary programming (EP) has been applied to many numerical and combinatorial optimisation prob-lems successfully in recent years. One disadvantage of EP is its slow some function propose a fast...
Evolutionary Framework for the Construction of Diverse Hybrid Ensembles (2008)
Abstract. Enforcing diversity explicitly in ensembles while at the same time making individual predictors accurate as well has been shown to be promising. This idea was recently taken into account in...
Abstract Digital Filter Design Using Multiple Pareto Fronts (2008)
Evolutionary approaches have been used in a large variety of design domains, from aircraft engineering to the designs of analog filters. Many of these approaches use measures to improve the variety...
Thorsten Schnier, Xin Yao, Russell Beale, Bob Hendley, Will Byrne
This paper presents an account of the nature inspired design research network. It discusses the potential benefits of researching and adopting nature inspired approaches in design. It summarises the...
DIVACE: Diverse and Accurate Ensemble Learning Algorithm (2008)
Abstract. In order for a neural network ensemble to generalise properly, two factors are considered vital. One is the diversity and the other is the accuracy of the networks that comprise the...
Robust Solution of Salting Route Optimisation Using Evolutionary Algorithms (2008)
Hisashi H, Dan Lin, Lee Chapman, Xin Yao
Abstract — The precautionary salting of the road network is an important maintenance issue for countries with a marginal winter climate. On many nights, not all the road network will require...
The Nature Inspired Creative Design network brings (2008)
Thorsten Schnier, Russell Beale, Xin Yao, Bob Hendley, Will Byrne
Evolving Cooperation in Complex Behavioral Interactions through Reputation (2008)
The iterated prisoner’s dilemma (IPD) has long been used to study the conditions that promote cooperative behaviors among selfish individuals. In particular, studies using the co-evolutionary...
Efficient Forward Regression with Marginal Likelihood (2008)
Abstract. We propose an efficient forward regression algorithm based on greedy optimization of marginal likelihood. It can be understood as a forward selection procedure which adds a new basis vector...
Teaching Advanced Features of Evolutionary Algorithms Using Japanese Puzzles (2008)
Abstract—In this paper, a method to teach advanced features of evolutionary algorithms (EAs), using a famous game known as Japanese puzzles is presented. The authors show that Japanese puzzles are...
Exploiting Coalition in Co-Evolutionary Learning (2008)
Yeon-gyu Se, Sung-bae Cho, Xin Yao
Abstract- Adaptive behaviors often emerge through in-teractions between adjacent neighbors in dynamic sys-tems, such as social and economic systems. In many cases, an individual’s behaviors can be...
An Improved Constructive Neural Network Ensemble Approach to Medical Diagnoses (2008)
Abstract. Neural networks have played an important role in intelligent medical diagnoses. This paper presents an Improved Constructive Neural Network Ensemble (ICNNE) approach to three medical...
A New Multi-objective Evolutionary Optimisation Algorithm: The Two-Archive Algorithm (2008)
Many Multi-Objective Evolutionary Algorithms (MOEAs) have been proposed in recent years. However, almost all MOEAs have been evaluated on problems with two to four objectives only. It is unclear how...
There is a widespread perception that in conflict situations, more intermediate choices between full peace and total war makes full peace less likely. This view is a motivation for opposing the...
Pietro S. Oliveto, Jun He, Xin Yao
Abstract: Computational time complexity analyzes of evolutionary algorithms (EAs) have been performed since the mid-nineties. The first results were related to very simple algorithms, such as the...
Application of Fuzzy Similarity to Prediction of Epileptic Seizures Using EEG Signals (2008)
Abstract. The prediction of epileptic seizures is a very attractive issue for all patients suffering from epilepsy in EEG (electroencephalograph) signals. It can assist to develop an intervention...
Ko-hsin Liang, Xin Yao, Charles S. Newton
Abstract. The lognormal self-adaptation has been used extensively in evolutionary programming (EP) and evolution strategies (ES) to adjust the search step size for each objective variable. However,...
SIMULATED ANNEALING AND JOINT MANUFACTURING BATCH-SIZING (2008)
Abstract: We address an important problem of a manufacturing system. The system procures raw materials from outside suppliers in a lot and processes them to produce finished goods. It proposes an...
On the clustering property of the random intersection graphs (2008)
A random intersection graph mtlmcalG_V,W,p is induced from a random bipartite graph mtlmcalG^*_V,W,p with vertices classes mtlV, mtlW and the edges incident between mtlv in V and mtlw in W with...
An Experimental Study of Hybridizing Cultural Algorithms and Local Search (2008)
www.bham.ac.uk In this paper the performance of the Cultural Algorithms Iterated Local Search (CA-ILS), a new continuous optimization algorithm, is empirically studied on multimodal test functions...
Search based software testing of object-oriented containers (2008)
Automatic software testing tools are still far from ideal for real world Object-Oriented (OO) Software. The use of nature inspired search algorithms for this problem has been investigated recently....
He, Jun, Zhou, Yuren, Yao, Xin
Constraints exist in almost every optimization problem. Different constraint handling techniques have been incorporated with genetic algorithms (GAs), however most of current studies are based on...
Quantum Spin Excitations through the metal-to-insulator crossover in $Y Ba_2 Cu_3 O_{6+y}$ (2007)
Li, Shiliang, Yamani, Zahra, Kang, Hye Jung, Segawa, Kouji, Ando, Yoichi, Yao, Xin, ...
We use inelastic neutron scattering to study the temperature dependence of the spin excitations of a detwinned superconducting YBa$_2$Cu$_3$O$_{6.45}$ ($T_c=48$ K). In contrast to earlier work on...
Accepted by International Journal of Intelligent Systems, to appear. (2007)
Research on potential interactions between connectionist learning systems, i.e., artificial neural networks (ANNs), and evolutionary search procedures, like genetic algorithms (GAs), has attracted a...
1 Solving Equations by Hybrid Evolutionary Computation Techniques (2007)
Evolutionary computation techniques have mostly been used to solve various optimisation and learning problems. This paper describes a novel application of evolutionary computation techniques to...
The Impact of Payo Function and Local Interaction on the N-player Iterated Prisoner's Dilemma (2007)
Yeon-gyu Seo, Sung-bae Cho, Xin Yao
The N-player iterated prisoner's dilemma (NIPD) game has been widely used to study the evolution of cooperation in social, economic and biological systems. This paper studies the impact of...
This paper examines the use of evolutionary methods in deriving comprehensible solutions in a relational problem domain. Evolution is used to manipulate a rule set with pre-dened relational functions...
This paper examines the use of evolutionary methods in deriving comprehensible solutions in a relational problem domain. Evolution is used to manipulate a rule set with pre-defined relational...
Automatic Discovery of Comprehensible Control Rules by Evolutionary Algorithms Jason Bobbin (2007)
Masoud Mohammadian (ed, Xin Yao
Computational intelligence techniques in control have facilitated the automatic generation of control strategies with little or no human input about the system. The present research examines the use...
A Preliminary Study Into Evolutionary Search of an Approximated N-Dimensional Landscape (2007)
Ko-Hsin Liang, Xin Yao, Charles Newton
Finding the global optimum on a large, multimodal, complex, and discontinuous (or nondifferentiable) landscape is usually very hard, even using the evolutionary approach. However, some of these...
Call Routing by Simulated Annealing 1 (2007)
Simulated Annealing (SA) is a powerful stochastic search algorithm applicable to a wide range of problems. This paper presents some experiments of applying SA to an NP-hard problem, i.e., call...
A Note on Neural Sorting Networks With O(1) Time Complexity (2007)
This is a follow-up note to Chen and Hsieh's recent paper [1]. It is indicated that there are two types of neural sorting networks with O(1) time complexity, both of which were published in 1990...
Artificial Intelligence 140 (2002) 245–248 Corrigendum (2007)
www.elsevier.com/locate/artint Erratum to: Drift analysis and average time complexity of evolutionary algorithms
Simulated Annealing (SA) is a powerful stochastic search method applicable to a wide range of problems for which little prior knowledge is available. It can produce very high quality solutions for...
Learning and evolution are two fundamental forms of adaptation. There has been a great interest in combining learning and evolution with artificial neural networks (ANN’s) in recent years. This...
1.1 Speciation in Co-evolutionary Learning (2007)
Abstract. Various extensions to the Genetic Algorithm (GA) attempt to find all or most optima in a search space containing several optima. Many of these emulate natural speciation. For...
Xin Yao, Manfred Fischer, Gavin Brown
It is well-known that large neural networks with many unshared weights can be very dicult to train. A neural network ensemble consisting of a number of individual neural networks usually performs...
1 An Empirical Study of Genetic Operators in Genetic Algorithms (2007)
Genetic algorithms are multi-agent search strategies applicable to a wide range of problems. However, it is often very dicult in practice to design an optimal set of genetic operators for a problem,...
Chapter 1 CONSTRAINED EVOLUTIONARY OPTIMIZATION (2007)
Thomas Philip Runarsson, Xin Yao
Abstract The penalty function method has been used widely in constrained evolutionary optimization (CEO). This chapter provides an in-depth analysis of the penalty function method from the point of...
Automatic Discovery of Comprehensible Control Rules by Evolutionary Algorithms (2007)
Masoud Mohammadian (ed, Jason Bobbin, Xin Yao
Abstract. Computational intelligence techniques in control have facilitated the automatic generation of control strategies with little or no human input about the system. The present research...
Real-world problems are often too difficult to be solved by a single monolithic system. Many natural and artificial systems use a modular approach to reduce the complexity of a set of subtasks while...
evolutionary computation (EC), genetic diversity (or the lack thereof) gets the credit (or the blame) for a multitude of effects--- and so mutation operators, population initialisation, and even...
Recent New Development in Evolutionary Programming (2007)
Evolutionary programming (EP) is one of the major branches of evolutionary computation. It has been applied to many learning and optimisation problems with success in recent years. This paper gives...
Exploiting Ensemble Diversity For (2007)
Automatic Feature Extraction, Gavin Brown, Xin Yao, Jeremy Wyatt, Heiko Wersing, Bernhard Sendhoff
We present an automatic method, based on a neural network ensemble, for extracting multiple, diverse and complementary sets of useful classification features from highdimensional data. We demonstrate...
computation time of evolutionary algorithms (2007)
an analytic framework for analysing the
A memetic algorithm for VLSI floorplanning (2007)
Floorplanning is an important problem in very large scale integrated-circuit (VLSI) design automation as it determines the performance, size, yield, and reliability of VLSI chips. From the...
A memetic algorithm for VLSI floorplanning (2007)
Floorplanning is an important problem in very largescale integrated-circuit (VLSI) design automation as it determinesthe performance, size, yield, and reliability of VLSI chips. Fromthe computational...
A memetic algorithm for VLSI floorplanning (2007)
Floorplanning is an important problem in very large scale integrated-circuit (VLSI) design automation as it determines the performance, size, yield, and reliability of VLSI chips. From the...
A memetic algorithm for VLSI floorplanning (2007)
Floorplanning is an important problem in very largescale integrated-circuit (VLSI) design automation as it determinesthe performance, size, yield, and reliability of VLSI chips. Fromthe computational...
A memetic algorithm for VLSI floorplanning (2007)
Floorplanning is an important problem in very large scale integrated-circuit (VLSI) design automation as it determines the performance, size, yield, and reliability of VLSI chips. From the...
A memetic algorithm for VLSI floorplanning (2007)
Floorplanning is an important problem in very large scale integrated-circuit (VLSI) design automation as it determines the performance, size, yield, and reliability of VLSI chips. From the...
A memetic algorithm for VLSI floorplanning (2007)
Floorplanning is an important problem in very large scale integrated-circuit (VLSI) design automation as it determines the performance, size, yield, and reliability of VLSI chips. From the...
A memetic algorithm for VLSI floorplanning (2007)
Floorplanning is an important problem in very large scale integrated-circuit (VLSI) design automation as it determines the performance, size, yield, and reliability of VLSI chips. From the...
A memetic algorithm for VLSI floorplanning (2007)
Floorplanning is an important problem in very large scale integrated-circuit (VLSI) design automation as it determines the performance, size, yield, and reliability of VLSI chips. From the...
A memetic algorithm for VLSI floorplanning (2007)
Floorplanning is an important problem in very large scale integrated-circuit (VLSI) design automation as it determines the performance, size, yield, and reliability of VLSI chips. From the...
A memetic algorithm for VLSI floorplanning (2007)
Floorplanning is an important problem in very large scale integrated-circuit (VLSI) design automation as it determines the performance, size, yield, and reliability of VLSI chips. From the...
A memetic algorithm for VLSI floorplanning (2007)
Floorplanning is an important problem in very large scale integrated-circuit (VLSI) design automation as it determines the performance, size, yield, and reliability of VLSI chips. From the...
A memetic algorithm for VLSI floorplanning (2007)
Floorplanning is an important problem in very large scale integrated-circuit (VLSI) design automation as it determines the performance, size, yield, and reliability of VLSI chips. From the...
A memetic algorithm for VLSI floorplanning (2007)
Floorplanning is an important problem in very large scale integrated-circuit (VLSI) design automation as it determines the performance, size, yield, and reliability of VLSI chips. From the...
A memetic algorithm for VLSI floorplanning (2007)
Floorplanning is an important problem in very large scale integrated-circuit (VLSI) design automation as it determines the performance, size, yield, and reliability of VLSI chips. From the...
A memetic algorithm for VLSI floorplanning (2007)
Floorplanning is an important problem in very large scale integrated-circuit (VLSI) design automation as it determines the performance, size, yield, and reliability of VLSI chips. From the...
Estimation of distribution algorithms for testing object oriented software (2007)
Ramón Sagarna, Andrea Arcuri, Xin Yao
Software
Distributed Transaction Management in SOA-based System Integration (2007)
Advisor Arne, John Glenstrup, Xin Yao
xin[at]itu.dk decorus[at]itu.dk
Intelligent Planning for Autonomous Underwater Vehicles (2007)
Zeyn A Saigol, Jeremy Wyatt (supervisor, Xin Yao, Minor Revisions
The aim of my PhD is to develop novel algorithms to allow an Autonomous Underwater Vehicle (AUV) to locate hydrothermal vents on the ocean floor. Hydrothermal vents are tectonically-driven...
Negative Correlation in Incremental Learning (2007)
A L. Minku, Hirotaka Inoue, Xin Yao
Negative Correlation Learning (NCL) has been successfully applied to construct neu-ral network ensembles. It encourages the neural networks that compose the ensemble to be different from each other...
PLEASE SCROLL DOWN FOR ARTICLE (2007)
Publisher Taylor, Registered Engl, Wales Registered Number, Jingsong He, Xin Yao, Yunbi Chen
Publication details, including instructions for authors and subscription information:
A memetic algorithm for VLSI floorplanning (2007)
Floorplanning is an important problem in very large scale integrated-circuit (VLSI) design automation as it determines the performance, size, yield, and reliability of VLSI chips. From the...
A memetic algorithm for VLSI floorplanning (2007)
Floorplanning is an important problem in very large scale integrated-circuit (VLSI) design automation as it determines the performance, size, yield, and reliability of VLSI chips. From the...
A memetic algorithm for VLSI floorplanning (2007)
Floorplanning is an important problem in very large scale integrated-circuit (VLSI) design automation as it determines the performance, size, yield, and reliability of VLSI chips. From the...
A memetic algorithm for VLSI floorplanning (2007)
Floorplanning is an important problem in very large scale integrated-circuit (VLSI) design automation as it determines the performance, size, yield, and reliability of VLSI chips. From the...
Robust Solution of Salting Route Optimisation Using Evolutionary Algorithms (2006)
Handa, Hisashi, Lin, Dan, Chapman, Lee, Yao, Xin
The precautionary salting of the road network is an important maintenance issue for countries with a marginal winter climate. On many nights, not all the road network will require treatment as the...
Robust Solution of Salting Route Optimisation Using Evolutionary Algorithms (2006)
Handa, Hisashi, Lin, Dan, Chapman, Lee, Yao, Xin
The precautionary salting of the road network is an important maintenance issue for countries with a marginal winter climate. On many nights, not all the road network will require treatment as the...
Gao, Hong, Ren, Cong, Shan, Lei, Wang, Yue, Zhang, Yingzi, Zhao, Shiping, ...
The temperature and field dependence of reversible magnetization have been measured on a YBa$_2$Cu$_3$O$_{7-\delta}$ single crystal at six different doping concentrations. It is found that the data...
Gene selection algorithms for microarray data based on least squares support vector machine (2006)
Tang, E Ke, Suganthan, PN, Yao, Xin
Abstract Background In discriminant analysis of microarray data, usually a small number of samples are expressed by a large number of genes. It is not only difficult but also unnecessary to conduct...
Robust route optimization for gritting/salting trucks: a CERCIA experience (2006)
Handa, Hisashi, Chapman, Lee, Yao, Xin
Highway authorities in marginal winter climates are responsible for the precautionary gritting/salting of the road network in order to prevent frozen roads. For efficient and effective road...
Robust route optimization for gritting/salting trucks: a CERCIA experience (2006)
Handa, Hisashi, Chapman, Lee, Yao, Xin
Highway authorities in marginal winter climates are responsible for the precautionary gritting/salting of the road network in order to prevent frozen roads. For efficient and effective road...
A Gradient-based Forward Greedy Algorithm for Sparse Gaussian Process Regression (2006)
Abstract In this chaper, we present a gradient-based forward greedy method for sparse approximation of Bayesian Gaussian Process Regression (GPR) model. Different from previous work, which is mostly...
Hybridizing Cultural Algorithms and Local Search (2006)
Abstract. In this paper, we propose a new population-based framework for combining local search with global explorations to solve single-objective unconstrained numerical optimization problems. The...
Greedy forward selection algorithms to sparse Gaussian Process Regression (2006)
Ping Sun, Student Member, Xin Yao
Abstract — This paper considers the basis vector selection issue invloved in forward selection algorithms to sparse Gaussian Process Regression (GPR). Firstly, we re-examine a previous basis vector...
Multiple choices and reputation in multiagent interactions (2006)
Abstract—Coevolutionary learning provides a framework for modeling more realistic iterated prisoner’s dilemma (IPD) interactions and to study conditions of how and why certain behaviors (e.g.,...
Greedy forward selection algorithms to sparse Gaussian Process Regression (2006)
Ping Sun, Student Member, Xin Yao
Abstract — This paper considers the basis vector selection issue invloved in forward selection algorithms to sparse Gaussian Process Regression (GPR). Firstly, we re-examine a previous basis vector...
An evolutionary clustering algorithm for gene expression microarray data analysis (2006)
Abstract—Clustering is concerned with the discovery of interesting groupings of records in a database. Many algorithms have been developed to tackle clustering problems in a variety of application...
A Gradient-based Forward Greedy Algorithm for Sparse Gaussian Process Regression (2006)
Abstract In this chaper, we present a gradient-based forward greedy method for sparse approximation of Bayesian Gaussian Process Regression (GPR) model. Different from previous work, which is mostly...
Diversity creation in local search for the evolution of neural network ensembles (2006)
Abstract. The EENCL algorithm [1] automatically designs neural network ensembles for classification, combining global evolution with local search based on gradient descent. Two mechanisms encourage...
An Exchanging-based Refinement to Sparse Gaussian Process Regression (2006)
We propose a backward deletion procedure to Sparse Gaussian Process Regression (SGPR) model, which can be used to refine a number of sequential forward selection algorithms addressed recently. Some...
Speeding Up Evolutionary Algorithms Through Restricted Mutation Operators (2006)
Doerr, Benjamin, Hebbinghaus, Nils, Neumann, Frank, Runarsson, Thomas Ph., Beyer, Hans G., Burke, Edmund, ...
We investigate the effect of restricting the mutation operator in evolutionary algorithms with respect to the runtime behavior. For the Eulerian cycle problem; we present runtime bounds on...
Dynamic salting route optimisation using evolutionary computation (2005)
Handa, Hisashi, Chapman, Lee, Yao, Xin
On marginal winter nights, highway authorities face a difficult decision as to whether or not to salt the road network. The consequences of making a wrong decision are serious, as an untreated...
Dynamic salting route optimisation using evolutionary computation (2005)
Handa, Hisashi, Chapman, Lee, Yao, Xin
On marginal winter nights, highway authorities face a difficult decision as to whether or not to salt the road network. The consequences of making a wrong decision are serious, as an untreated...
X.: Search biases in constrained evolutionary optimization (2005)
Thomas Philip Runarsson, Xin Yao
Abstract — A common approach to constraint handling in evolutionary optimization is to apply a penalty function to bias the search towards a feasible solution. It has been proposed that the...
Diversity creation methods: A survey and categorisation (2005)
Gavin Brown, Jeremy Wyatt, Rachel Harris, Xin Yao
Ensemble approaches to classification and regression have attracted a great deal of interest in recent years. These methods can be shown both theoretically and empirically to outperform single...
This paper compares three different evolutionary algorithms for solving the node covering problem: EA-I relies on the definition of the problem only without using any domain knowledge, while EA-II...
Abstract—This paper compares three different evolutionary algorithms for solving the node covering problem:EA-I relies on the definition of the problem only without using any domain knowledge,...
Volatility Forecasting with Sparse Bayesian Kernel Models (2005)
Peter Tiňo, Nikolay Nikolaev, Xin Yao
Motivated by previous findings that discretization of financial time series can effectively filter the data and reduce the noise, this experimental study, performed in a realistic setting of trading...
Global optimisation Evolutionary neural networks Evolutionary algorithms Genetic algorithms (2005)
Xin Yao, Yong Liu, Jin Li, Jun He, Colin Frayn
developments and future directions of bio-inspired
Sancho Salcedo-sanz, O Cruz-roldán, Senior Member, Conor Heneghan, Xin Yao
Abstract—In this paper, two evolutionary programming (EP) algorithms (classical EP and fast EP) are applied to design prototype lowpass Finite Impulse Response filters for use in a modulated...
Yong Xu, Sancho Salcedo-sanz, Xin Yao
The widespread deployment of WDM optical networks posts lots of new challenges for network designers. Traffic grooming is one of the most common problems. Efficient grooming of traffic can...
Co-evolutionary modular neural networks for automatic problem decomposition (2005)
Abstract- Decomposing a complex computational problem into sub-problems, which are computationally simpler to solve individually and which can be combined to produce a solution to the full problem,...
X.: Search biases in constrained evolutionary optimization (2005)
Thomas Philip Runarsson, Xin Yao
Abstract—A common approach to constraint handling in evolutionary optimization is to apply a penalty function to bias the search toward a feasible solution. It has been proposed that the subjective...
A game-theoretic approach for designing mixed mutation strategies (2005)
Abstract. Different mutation operators have been proposed in evolutionary programming. However, each operator may be efficient in solving a subset of problems, but will fail in another one. Through a...
Behavioral diversity, choices, and noise in the iterated prisoner’s dilemma (2005)
Abstract—Real-world dilemmas rarely involve just two choices and perfect interactions without mistakes. In the iterated prisoner’s dilemma (IPD) game, intermediate choices or mistakes (noise)...
Diversity creation methods: A survey and categorisation (2005)
Gavin Brown, Jeremy Wyatt, Rachel Harris, Xin Yao
Ensemble approaches to classification and regression have attracted a great deal of interest in recent years. These methods can be shown both theoretically and empirically to outperform single...
Co-evolutionary modular neural networks for automatic problem decomposition (2005)
Abstract- Decomposing a complex computational problem into sub-problems, which are computationally simpler to solve individually and which can be combined to produce a solution to the full problem,...
A game-theoretic approach for designing mixed mutation strategies (2005)
Abstract. Different mutation operators have been proposed in evolutionary programming. A mixture of various mutation operators may be more efficient than a single one. This paper presents a...
Governance mechanisms of urban fringe land use in China : a case study of Nanjing (2004)
(Uncorrected OCR) Abstract of dissertation entitled Governance Mechanisms of Urban Fringe Land Use in China: A Case Study of Nanjing Submitted by Xin Yao for the degree of Doctor of Philosophy at the...
Governance mechanisms of urban fringe land use in China : a case study of Nanjing (2004)
(Uncorrected OCR) Abstract of dissertation entitled Governance Mechanisms of Urban Fringe Land Use in China: A Case Study of Nanjing Submitted by Xin Yao for the degree of Doctor of Philosophy at the...
Governance mechanisms of urban fringe land use in China : a case study of Nanjing (2004)
(Uncorrected OCR) Abstract of dissertation entitled Governance Mechanisms of Urban Fringe Land Use in China: A Case Study of Nanjing Submitted by Xin Yao for the degree of Doctor of Philosophy at the...
Digital filter design using multiple pareto fronts (2004)
Thorsten Schnier, Xin Yao, Pin Liu
Abstract Evolutionary approaches have been used in a large variety of design domains, from aircraft engineering to the designs of analog filters. Many of these approaches use measures to improve the...
DIVACE: diverse and accurate ensemble learning algorithm (2004)
Arjun Chandra, Supervisor Prof, Xin Yao
Evolutionary framework for the creation of diverse hybrid ensembles for better generalisation
Abstract. In this paper we present three meta-heuristic approaches for FPGA segmented channel routing problems (FSCRPs) with a new cost function in which the cost of each assignment is not known in...
Digital filter design using multiple pareto fronts (2004)
Evolutionary approaches have been used in a large variety of design domains, from aircraft engineering to the designs of analog filters. Many of these approaches use measures to improve the variety...
Diversity Creation Methods: A Survey And Categorisation (2004)
Gavin Brown, Jeremy Wyatt, Rachel Harris, Xin Yao
Ensemble approaches to classification and regression have attracted a great deal of interest in recent years. These methods can be shown both theoretically and empirically to outperform single...
Evolutionary Programming Using Mutations Based on the Lévy Probability Distribution (2004)
This paper studies evolutionary programming with mutations based on the Lvy probability distribution. The Lvy probability distribution has an infinite second moment and is, therefore, more likely to...
An evolutionary approach to modeling radial brightness distributions in elliptical galaxies (2004)
Jin Li, Xin Yao, Colin Frayn, Habib G. Khosroshahi, Somak Raychaudhury
Abstract. A reasonably good description of the luminosity profiles of galaxies is needed as it serves as a guide towards understanding the process of galaxy formation and evolution. To obtain a...
A hybrid Hopfield network-genetic algorithm approach for the terminal assignment problem (2004)
Abstract—This paper presents a hybrid Hopfield network-genetic algorithm (GA) approach to tackle the terminal assignment (TA) problem. TA involves determining minimum cost links to form a...
Credit assignment among neurons in co-evolving populations (2004)
Vineet R. Khare, Xin Yao, Bernhard Sendhoff
WWW home page:http://www.honda-ri.de Abstract. Different credit assignment strategies are investigated in a two level co-evolutionary model which involves a population of Gaussian neurons and a...
Towards an Analytic Framework for Analysing the Computation Time of Evolutionary Algorithms (2003)
In spite of many applications of evolutionary algorithms in optimisation, theoretical results on the computation time and time complexity of evolutionary algorithms on different optimisation problems...
Computational Intelligence in Control (2003)
Mohamadian, Masoud, Sarker, Ruhul Amin, Yao, Xin
Obra sobre las aplicaciones de las técnicas de inteligencia computacional para modelar y solucionar problemas relativos con el control y la automatización. Entre otros, aborda los siguientes temas:...
Computational Intelligence in Control (2003)
Mohamadian, Masoud, Sarker, Ruhul Amin, Yao, Xin
1-59140-037-6
Using negative correlation to evolve fault-tolerant circuits (2003)
Abstract. In this paper, we show how artificial evolution can be used to improve the fault-tolerance of electronic circuits. We show that evolution is able to improve the fault tolerance of a digital...
Towards an analytic framework for analysing the computation time of evolutionary algorithms (2003)
In spite of many applications of evolutionary algorithms in optimisation, theoretical results on the computation time and time complexity of evolutionary algorithms on different optimisation problems...
Abstract. In practice, evolutionary algorithms are often used to find good feasible solutions to complex optimisation problems in a reasonable running time, rather than the optimal solutions. In...
A Constructive Algorithm for Training Cooperative Neural Network Ensembles (2003)
Md. Monirul Islam, Xin Yao, Kazuyuki Murase
This paper presents a constructive algorithm for training cooperative neural-network ensembles (CNNEs). CNNE combines ensemble architecture design with cooperative training for individual neural...
On the Architectures of Complex Multi-Agent Systems (2003)
H. Tianfield, Huaglory Tianfield, Jiang Tian, Xin Yao
This paper presents a literature review on the architectures of complex multi-agent systems. Firstly, the concept of general architectures and three orientations of systems architectures, i.e.,...
Materialized View Selection as Constrained (2003)
Evolutionary Optimization Jeffrey, Jeffrey Xu Yu, Xin Yao, Chi-hon Choi, Gang Gou
One of the important issues in data warehouse development is the selection of a set of views to materialize in order to accelerate a large number of on-line analytical processing (OLAP) queries. The...
Dual Population-Based Incremental Learning for Problem Optimization in Dynamic Environments (2003)
In recent years there is a growing interest in the research of evolutionary algorithms for dynamic optimization problems since real world problems are usually dynamic, which presents serious...
Performance scaling of multi-objective evolutionary algorithms (2003)
Vineet R. Khare, Xin Yao, Kalyanmoy Deb
• Algorithms used • Test problems • Performance metrics
Almost all analyses of time complexity of evolutionary algorithms (EAs) have been conducted for (1 + 1) EAs only. Theoretical results on the average computation time of population-based EAs are few....
Maximum cardinality matching by evolutionary algorithms (2002)
The analysis of time complexity of evolutionary algorithms has always focused on some artificial binary problems. This paper considers the average time complexity of an evolutionary algorithm for...
Almost all analyses of time complexity of evolutionary algorithms (EAs) have been conducted for (1+1) EAs only. Theoretical results on the average computation time of population-based EAs are few....
A new evolutionary approach to cutting stock problems with and without contiguity (2002)
Ko-hsin Liang, Xin Yao, Charles Newton
Evolutionary algorithms (EAs) have been applied to many optimization problems successfully in recent years. The genetic algorithm (GAs) and evolutionary programming (EP) are two dierent types of EAs....
There is a widespread perception that in conict situations, more intermediate choices between full peace and total war makes full peace less likely. This view is a motivation for opposing the...
Suif compiler framework http://suif.stanford.edu (2002)
Abstract. This paper presents a methodology for applying the principles of evolutionary computation to knowledge discovery in databases by evolving SQL queries that describe datasets. In our system,...
Artificial speciation of neural network ensembles (2002)
• Overview of the methodology
Thesis (Ph. D.)--University of Southern California, 2002.
Drift analysis and average time complexity of evolutionary algorithms (2001)
The computational time complexity is an important topic in the theory of evolutionary algorithms (EAs). This paper reports some new results on the average time complexity of EAs. Based on drift...
Evolutionary design calibration (2001)
Abstract. Evolutionary methods are now beginning to be used routinely in design applications. However, even with computing speeds growing continuously, for many complex design problems evolutionary...
On the E#ectiveness of Negative Correlation Learning (2001)
Neural network ensembles are well accepted as a route to combining a group of weaker learning systems in order to make a composite, stronger one. It has been shown that low correlation of errors...
Drift analysis and average time complexity of evolutionary algorithms (2001)
The computational time complexity is an important topic in the theory of evolutionary algorithms (EAs). This paper reports some new results on the average time complexity of EAs. Based on drift...
An evolutionary approach to materialized views selection in a data warehouse environment (2001)
Chuan Zhang, Xin Yao, Senior Member, Jian Yang
Abstract—A data warehouse (DW) contains multiple views accessed by queries. One of the most important decisions in designing a DW is selecting views to materialize for the purpose of efficiently...
Adapting self-adaptive parameters in evolutionary algorithms (2001)
Ko-hsin Liang, Xin Yao, Charles S. Newton
The lognormal self-adaptation has been used extensively in evolutionary programming (EP) and evolution strategies (ES) to adjust the search step size for each objective variable. However, it was...
An evolutionary approach to materialized views selection in a data warehouse environment (2001)
Chuan Zhang, Xin Yao, Jian Yang
A data warehouse contains multiple views accessed by queries. One of the most important decisions in designing a data warehouse is selecting views to materialize for the purpose of eciently...
Why more choices cause less cooperation in iterated prisoner’s dilemma (2001)
Iterated Prisoner's Dilemma (IPD) has only 2 choices, cooperate or defect. However, most real-world situations offer intermediate responses, between full cooperation and full defection. Previous...
Drift analysis and average time complexity of evolutionary algorithms (2001)
The computational time complexity is an important topic in the theory of evolutionary algorithms (EAs). This paper reports some new results on the average time complexity of EAs. Based on drift...
Why More Choices Cause Less Cooperation in Iterated Prisoner's Dilemma (2001)
This paper demonstrates two mechanisms that sabotage the emergence of full mutual cooperation. First, to increase cooperation requires behavioral (phenotypic) diversity to explore different possible...
Scaling Up Fast Evolutionary Programming with Cooperative Coevolution (2001)
Yong Liu, Xin Yao, Qiangfu Zhao
Evolutionary programming (EP) has been applied with success to many numerical and combinatorial optimization problems in recent years. However, most analytical and experimental results on EP have...
Evolving a Cooperative Population of Neural Networks by Minimizing Mutual Information (2001)
Yong Liu, Xin Yao, Qiangfu Zhao
Evolutionary ensembles with negative correlation learning (EENCL) is an evolutionary learning system for learning and designing neural network ensembles [1]. The fitness sharing used in EENCL was...
Parallel Problem Solving from Nature - PPSN VI (2000)
Schoenauer, Marc, Lutton, Evelyne, Deb, Kalyanmoy, Rudolph, Guenter, Yao, Xin, Merelo, Juan Julian, ...
Parallel Problem Solving from Nature - PPSN VI (2000)
Schoenauer, Marc, Lutton, Evelyne, Deb, Kalyanmoy, Rudolph, Guenter, Yao, Xin, Merelo, Juan Julian, ...
Solving equations by hybrid evolutionary computation techniques (2000)
Evolutionary computation techniques have mostly been used to solve various optimisation and learning problems. This paper describes a novel application of evolutionary computation techniques to...
Evolutionary ensembles with negative correlation learning (2000)
Yong Liu, Xin Yao, Tetsuya Higuchi
Based on negative correlation learning and evolutionary learning, this paper presents evolutionary ensembles with negative correlation learning (EENCL) to address the issues of automatic...
Stochastic ranking for constrained evolutionary optimization (2000)
Thomas Philip Runarsson, Xin Yao
Penalty functions are often used in constrained optimization. However, it is very dicult to strike the right balance between objective and penalty functions. This paper introduces a novel approach to...
Genetic Algorithms and Evolutionary Games (2000)
Genetic algorithms (GAs) have been used widely in evolving game-playing strategies since the mid-1980's. This paper looks at a particular game--- the iterated prisoner's dilemma game, which...
Does Extra Genetic Diversity Maintain Escalation in a Co-Evolutionary Arms Race (2000)
In evolutionary computation (EC), genetic diversity (or its absence) gets the credit (or the blame) for a multitude of effects --- and so mutation operators, population initialization, and even...
Evolutionary Optimization Thomas, Thomas Philip Runarsson, Xin Yao
Penalty functions are often used in constrained optimization. However, it is very di#cult to strike the right balance between objective and penalty functions. This paper introduces a novel approach...
Marketing and Interdependent behaviour (2000)
This paper concentrates on the more complex and rich NIPD where N can be as large as 16. Three major issues will be investigated; (1) Can cooperation emerge from a population of random strategies? In...
Evolutionary Search of Approximated N-Dimensional Landscapes (2000)
Ko-Hsin Liang, Xin Yao, Charles Newton
Finding the global optimum on a large, multimodal, complex, and discontinuous (or nondifferentiable) landscape is usually very hard, even using the evolutionary approach. However, some of these...
Exploiting Coalition in Co-Evolutionary Learning (2000)
Yeon-Gyu Seo, Sung-Bae Cho, Xin Yao
Adaptive behaviors often emerge through interactions between adjacent neighbors in dynamic systems, such as social and economic systems. In many cases, an individual's behaviors can be modeled...
Using Multiple Representations in Evolutionary Algorithms (2000)
Although evolutionary algorithms are very different from other artificial intelligence search algorithms, they face similar fundamental issues --- representation and search. There have been a large...
Evolutionary programming made faster (1999)
Xin Yao, Senior Member, Yong Liu, Student Member, Guangming Lin
Abstract — Evolutionary programming (EP) has been applied with success to many numerical and combinatorial optimization problems in recent years. EP has rather slow convergence rates, however, on...
Simultaneous training of negatively correlated neural networks in an ensemble (1999)
Yong Liu, Student Member, Xin Yao, Senior Member
Abstract — This paper presents a new cooperative ensemble learning system (CELS) for designing neural network ensembles. The idea behind CELS is to encourage different individual networks in an...
The GRD Chip: Genetic reconfiguration of DSPs for Neural Network Processing (1999)
Masahiro Murakawa, Shuji Yoshizawa, Isamu Kajitani, Xin Yao, Senior Member, Nobuki Kajihara, ...
AbstractÐThis paper describes the GRD (Genetic Reconfiguration of DSPs) chip, which is evolvable hardware designed for neural network applications. The GRD chip is a building block for the...
How important is your reputation in a multi-agent environment (1999)
Most work on the evolutionary approach to the iterated prisoner 's dilemma (IPD) game uses a binary model where the choice of each player can only be cooperation or defection. However, we rarely...
Evolving rules for nonlinear control (1999)
Computational intelligence techniques in control have facilitated the automatic generation of control strategies with little or no human input about the system. The present research examines the use...
Universal Approximation by Genetic Programming (1999)
Genetic programming (GP) has been applied successfully to many difficult problems. However, little theory is currently available to explain why GP works or does not work for a particular problem. We...
Combining Landscape Approximation and Local Search in Global Optimization (1999)
Ko-Hsin Liang, Xin Yao, Charles Newton
Local search techniques have been applied in variant global optimization methods. The effect of local search to the function landscape can make multimodal problems easier to solve. For evolutionary...
How Does Evolutionary Computation Fit Into IT Postgraduate Teaching (1999)
Evolutionary computation courses have been offered by a wide range of departments/schools to students with many different backgrounds. This paper describes three postgraduate courses with significant...
Neural Networks for Breast Cancer Diagnosis (1999)
Breast cancer diagnosis has been approached by various machine learning techniques for many years. This paper describes two neural network based approaches to breast cancer diagnosis, both of which...
Evolving Materialized Views in Data Warehouse (1999)
Chuan Zhang, Xin Yao, Jian Yang
A data warehouse contains multiple views accessed by queries. One of the most important decisions in designing a data warehouse is the selection of materialized views for the purpose of efficiently...
Knowledge Extracted From Trained Neural Networks (1999)
Learning and evolution are two fundamental forms of adaptation. There has been a great interest in combining learning and evolution with artificial neural networks (ANNs) in recent years. This paper...
Ensemble Learning via Negative Correlation (1999)
This paper presents a learning approach, i.e., negative correlation learning, for neural network ensembles. Unlike previous learning approaches for neural network ensembles, negative correlation...
How important is your reputation in a multi-agent environment (1999)
Most work on the evolutionary approach to the iterated pris-oner’s dilemma (IPD) game uses a binary model where the choice of each player can only be cooperation or defection. However, we rarely...
Neural networks for breast cancer diagnosis (1999)
Abstract- Breast cancer diagnosis has been ap-proached by various machine learning techniques for many years. This paper describes two neural network based approaches to breast cancer diag-nosis,...
Emergence of cooperative coalition in NIPD game with localization of interaction and learning (1999)
Yeon-gyu Seo, Sung-bae Cho, Xin Yao
Abstract- The N-player iterated prisoner’s dilemma (NIPD) game has been used widely to study the evolution of cooperation in social, economic and biological systems. Previous work on the NIPD game...
Combining landscape approximation and local search in global optimization (1999)
Ko-hsin Liang, Xin Yao, Charles Newton
Abstract- Local search techniques have been ap-plied in variant global optimization methods. The effect of local search to the function land-scape can make multimodal problems easier to solve. For...
Towards Designing Artificial Neural Networks by Evolution (1998)
Designing artificial neural networks (ANNs) for different applications has been a key issue in the ANN field. At present, ANN design still relies heavily on human experts who have sufficient...
Making use of population information in evolutionary artificial neural networks (1998)
Xin Yao, Senior Member, Yong Liu, Student Member
Abstract—This paper is concerned with the simultaneous evolution of artificial neural network (ANN) architectures and weights. The current practice in evolving ANN’s is to choose the best ANN in...
Maximum matching on Boltzmann machines (1998)
The Boltzmann machine is one of the most popular neural network models used to cope with difficult combinatorial optimisation problems. It has been used to find near optimum solutions to such hard...
Dynamic Control of Adaptive Parameters in Evolutionary Programming (1998)
Ko-hsin Liang, Xin Yao, Charles Newton
Abstract. Evolutionary programming (EP) has been widely used in numerical optimization in recent years. The adaptive parameters, also named step size control, in EP play a significant role which...
Towards Designing Neural Network Ensembles by Evolution (1998)
. This paper proposes a co-evolutionary learning system, i.e., CELS, to design neural network (NN) ensembles. CELS addresses the issue of automatic determination of the number of individual NNs in an...
Scaling Up Evolutionary Programming Algorithms (1998)
. Most analytical and experimental results on evolutionary programming (EP) are obtained using low-dimensional problems, e.g., smaller than 50. It is unclear, however, whether the empirical results...
Simultaneous Learning of Negatively Correlated Neural Networks (1998)
A new approach to designing neural network ensembles has been proposed recently [1]. Experimental studies on some regression tasks have shown that the new approach performs significantly better than...
Negatively Correlated Neural Networks for Classification (1998)
A new approach to designing neural network ensembles has been proposed recently [1]. Experimental studies on some regression tasks have shown that the new approach performs significantly better than...
A Cooperative Ensemble Learning System (1998)
This paper presents a new cooperative ensemble learning system (CELS) for designing neural network ensembles. The idea behind CELS is to encourage different individual networks in an ensemble to...
PEPNet: parallel evolutionary programming for constructing artificial neural networks (1997)
Gerrit A. Riessen, Graham J. Williams, Xin Yao
This paper presents a description of an evolutionary artificial neural network algorithm, EP-Net and its extension taking advantage of a High Performance Computing Environment. PEP-Net, Parallel...
A new evolutionary system for evolving artificial neural networks (1997)
This paper presents a new evolutionary system, i.e., EPNet, for evolving artificial neural networks (ANNs). The evolutionary algorithm used in EPNet is based on Fogel's evolutionary programming...
Fast evolution strategies (1997)
Evolution strategies are a class of general optimisation algorithms which are applicable to functions that are multimodal, nondifferentiable, or even discontinuous. Although recombination operators...
Global optimisation by evolutionary algorithms (1997)
Evolutionary algorithms (EAs) are a class of stochastic search algorithms applicable to a wide range of problems in learning and optimisation. They have been applied to numerous problems in...
PEPNet: Parallel Evolutionary Programming for Constructing Artificial Neural Networks (1997)
Gerrit A. Riessen, Graham J. Williams, Xin Yao
This paper presents a description of an evolutionary artificial neural network algorithm, EPNet and its extension taking advantage of a High Performance Computing Environment. PEPNet, Parallel EPNet,...
Solving Optimal Control Problems with a Cost on Changing Control by Evolutionary Algorithms (1997)
Many mathematical solutions to certain classes of optimal control problems, particularly problems which give rise to `chattering controls', make some physically unrealistic assumptions in order...
EPNet for Chaotic Time-Series Prediction (1997)
. EPNet is an evolutionary system for automatic design of artificial neural networks (ANNs) [1, 2, 3]. Unlike most previous methods on evolving ANNs, EPNet puts its emphasis on evolving ANN's...
Evolving Modular Neural Networks Which Generalise Well (1997)
In dealing with complex problems, a monolithic neural network often becomes too large and complex to design and manage. The only practical way is to design modular neural network systems consisting...
The Importance of Maintaining Behavioural Link Between Parents and Offspring (1997)
In a recent study of evolutionary artificial neural networks (EANNs) [1], it has been argued that a partial training process after an architectural mutation plays an important role in maintaining the...
Analysing Crossover Operators by Search Step Size (1997)
Crossover plays an important role in GA-based search. There have been many empirical comparisons of different crossover operators in the literature. However, analytical results are limited. No theory...
Fast Evolution Strategies (1997)
. Evolution strategies are a class of general optimisation algorithms which are applicable to functions that are multimodal, nondifferentiable, or even discontinuous. Although recombination operators...
One of the major issues in the field of artificial neural networks (ANNs) is the design of their architectures. There are strong biological and engineering evidences to support that the information...
Exploiting population information in evolutionary learning (1996)
Xin Yao, Yong Liu, Paul Darwen
Evolutionary learning has been developing rapidly in the last decade. It is a powerful and general learning approach which has been used successfully in both symbolic systems, e.g., rule-based...
Evolutionary Programming Made Faster (1996)
Xin Yao, Yong Liu, Guangming Lin
Evolutionary programming (EP) has been applied with success to many numerical and combinatorial optimization problems in recent years. However, EP has rather slow convergence rates on some function...
How to Make Best Use of Evolutionary Learning (1996)
Xin Yao, Yong Liu, Paul Darwen
Evolutionary learning has been developing rapidly in the last decade. It is a powerful and general learning approach which has been used successfully in both symbolic systems, e.g., rule-based...
Automatic Modularization by Speciation (1996)
Real-world problems are often too difficult to be solved by a single monolithic system. There are many examples of natural and artificial systems which show that a modular approach can reduce the...
Promises and Challenges of Evolvable Hardware (1996)
. Evolvable hardware (EHW) has attracted increasing attentions since early 1990's with the advent of easily reconfigurable hardware such as field programmable gate array (FPGA). It promises to...
Towards Designing Artificial Neural Networks by Evolution (1996)
Designing artificial neural networks (ANNs) for different applications has been a key issue in the ANN field. Although there are many training algorithms available for learning ANN's connection...
Evolutionary Design of Artificial Neural Networks with Different Nodes (1996)
Evolutionary design of artificial neural networks (ANNs) offers a very promising and automatic alternative to designing ANNs manually. The advantage of evolutionary design over the manual design is...
Evolving Artificial Neural Networks Through Evolutionary Programming (1996)
Artificial neural network (ANN) architecture design has been one of the most tedious and difficult tasks in ANN applications due to the lack of satisfactory and systematic methods of designing a near...
Parallel Genetic Algorithm On Pvm (1996)
Guangming Lin, Xin Yao, Iain Macleod, Lishan Kang, Yuping Chen
In this paper we describe an implementation of some kinds of parallel genetic algorithms on the PVM, Parallel Virtual Machine, a portable parallel environment. We give details of a genetic algorithm...
Ensemble Structure of Evolutionary Artificial Neural Networks (1996)
Evolutionary artificial neural networks (EANNs) refer to a special class of artificial neural networks (ANNs) in which evolution is another fundamental form of adaptation in addition to learning....
Every Niching Method has its Niche: Fitness Sharing and Implicit Sharing Compared (1996)
Several extensions to the GA attempt to find all or most optima in a search space containing multiple optima. Many of these methods emulate speciation in natural evolution. Such methods must find all...
Evolutionary stability in the N-person iterated prisoner's dilemma (1996)
The iterated prisoner's dilemma game has been used extensively in the study of the evolution of cooperative behaviours in social and biological systems. The concept of evolutionary stability...
An Overview of Evolutionary Computation (1996)
This paper presents a brief overview of the field of evolutionary computation. Three major research areas of evolutionary computation will be discussed; evolutionary computation theory, evolutionary...
Evolutionary Artificial Neural Networks that Learn and Generalise Well (1996)
Evolutionary artificial neural networks (EANNs) refer to a special class of artificial neural networks (ANNs) in which evolution is another fundamental form of adaptation in addition to learning. The...
Fast Evolutionary Programming (1996)
Evolutionary programming (EP) has been applied to many numerical and combinatorial optimisation problems successfully in recent years. One disadvantage of EP is its slow convergence to a good near...
A dilemma for fitness sharing with a scaling function (1995)
Fitness sharing has been used widely in genetic algorithms for multi-objective function opti-mization and machine learning. It is often implemented with a scaling function, which adjusts an...
A dilemma for fitness sharing with a scaling function (1995)
Fitness sharing has been used widely in genetic algorithms for multi-objective function optimization and machine learning. It is often implemented with a scaling function, which adjusts an...
A Dilemma for Fitness Sharing with a Scaling Function (1995)
Fitness sharing has been used widely in genetic algorithms for multi-objective function optimization and machine learning. It is often implemented with a scaling function, which adjusts an...
A Preliminary Study on Designing Artificial Neural Networks Using Co-Evolution (1995)
The design of optimal artificial neural networks (ANNs) is a key issue in the study of ANNs from the point of view of both theory and applications. There are strong biological and engineering...
Evolving Artificial Neural Networks for Medical Applications (1995)
Artificial neural network (ANN) architecture design has been one of the most tedious and difficult tasks in ANN applications due to the lack of satisfactory and systematic methods of designing a near...
How Good is Fitness Sharing with a Scaling Function (1995)
Fitness sharing has been used widely in genetic algorithms for multi-objective function optimization and machine learning. It is often implemented with a scaling function, which adjusts an...
An experimental study of N-person iterated prisoner's dilemma games (1994)
The Iterated Prisoner's Dilemma game has been used extensively in the study of the evolution of cooperative behaviours in social and biological systems. There have been a lot of experimental...
An Experimental Study of N-Person Iterated Prisoner's Dilemma Games (1994)
The Iterated Prisoner's Dilemma game has been used extensively in the study of the evolution of cooperative behaviours in social and biological systems. There have been a lot of experimental...
An experimental study of N-person iterated prisoner's dilemma games (1994)
Abstract. The Iterated Prisoner’s Dilemma game has been used extensively in the study of the evolution of cooperative behaviours in social and biological systems. There have been a lot of...
A review of evolutionary artificial neural networks (1993)
Evolutionary Artificial Neural Networks (EANNs) can be considered as a combination of artificial neural networks (ANNs) and evolutionary search procedures, such as genetic algorithms (GAs). This...
Comparison of Different Neighbourhood Sizes in Simulated Annealing (1993)
Neighbourhood structure and size are important parameters in local search algorithms. This is also true for generalised local search algorithms like simulated annealing. It has been shown that the...
A Review of Evolutionary Artificial Neural Networks (1993)
Research on potential interactions between connectionist learning systems, i.e., artificial neural networks (ANNs), and evolutionary search procedures, like genetic algorithms (GAs), has attracted a...
Evolutionary Artificial Neural Networks (1993)
Evolutionary artificial neural networks (EANNs) [1] result from combinations of artificial neural networks (ANNs) and evolutionary search procedures such as genetic algorithms (GAs). This article...
Finding approximate solutions to NP-hard problems by neural networks is hard (1992)
Finding approximate solutions to hard combinatorial optimization problems by neural networks is a very attractive prospect. Many empirical studies have been done in the area. However, recent research...
Dynamic neighbourhood size in simulated annealing (1992)
Simulated annealing has been shown to be a powerful stochastic method of tackling hard combinatorial optimisation problems, but it demands a vast amount of computation time to arrive at a good...
Finding Approximate Solutions to NP-Hard Problems by Neural Networks Is Hard (1992)
Finding approximate solutions to hard combinatorial optimization problems by neural networks is a very attractive prospect. Many empirical studies have been done in the area. However, recent research...
Simulated Annealing with Extended Neighbourhood (1991)
Simulated Annealing (SA) is a powerful stochastic search method applicable to a wide range of problems for which little prior knowledge is available. It can produce very high quality solutions for...
Optimization by Genetic Annealing (1991)
Simulated Annealing (SA) is a general stochastic search algorithm. It is usually employed as an optimization method to find a near optimal solution for hard combinatorial optimization problems, but...
Following the Path of Evolvable Hardware (0000)
Evolvable hardware (EHW) refers to one particular type of hardware whose architecture, structure and functions change dynamically and autonomously in order to improve its performance in performing...
Following the Path of Evolvable Hardware
Evolvable hardware (EHW) refers to one particular type of hardware whose architecture, structure and functions change dynamically and autonomously in order to improve its performance in performing...
Lu, Mengji, Yao, Xin, Xu, Yang, Lorenz, Heike, Dahmen, Uta, Chi, Haidong, ...
The essential role of multispecific immune responses for the control of hepatitis B virus (HBV) infection implies the need of multimodal therapeutic strategies for chronic HBV infection, including...
Automatic Acquisition of Strategies by Co-evolutionary Learning
Co-evolutionary learning is a new learning approach emerged in recent years. It is designed to deal with dynamic learning tasks, i.e., the target to be learned changes over time. Such learning...
An Analysis of Evolutionary Algorithms Based on Neighbourhood and Step Sizes
Xin Yao, Guangming Lin, Yong Liu
. Evolutionary algorithms (EAs) can be regarded as algorithms based on neighbourhood search, where different search operators (such as crossover and mutation) determine different neighbourhood and...
Maneechotesuwan, Kittipong, Yao, Xin, Ito, Kazuhiro, Jazrawi, Elen, Usmani, Omar S., Adcock, Ian M., ...
Peter Barnes and colleagues show that corticosteroids have a potent inhibitory effect on GATA-3 via two interacting mechanisms that suppress Th2 cytokine expression. This novel mechanism of...