Jonathan E. Rowe

Tight bounds for blind search on the integers (2008)

Dietzfelbinger, Martin, Rowe, Jonathan E., Wegener, Ingo, Woelfel, Philipp

We analyze a simple random process in which a token is moved in the interval $A={0,dots,n$: Fix a probability distribution $mu$ over ${1,dots,n$. Initially, the token is placed in a random position...

Research Student Monitoring Group (2008)

Name Trung, Thanh Nguyen, Jonathan E. Rowe, Dr. Ata Kaban

Working title: Incorporating cultural knowledge and local search into evolutionary optimisation

El Botellón: Modeling the Movement of Crowds in a City (2008)

Jonathan E. Rowe, Rocio Gomez

A simulation of crowd movement in a city is studied under various assumptions about interactions between people. We find, in general, that there are two modes of steady-state behavior. The crowd may...

Abbreviations: GAs (2008)

Jonathan E. Rowe

Abstract. It is known that modelling a finite population genetic algorithm as a Markov chain requires a prohibitively large number of states. In an attempt to resolve this problem, a number of state...

State aggregation and population dynamics in (2008)

Linear Systems Jonathan, Jonathan E. Rowe, Alden H. Wright, Michael D. Vose

We consider complex systems that are comprised of many interacting elements, evolving under some dynamics. We are interested in characterizing the ways in which these elements may be grouped into...

Group Properties of Crossover and Mutation Jonathan E. Rowe (2008)

School Of Computer, Jonathan E. Rowe, Michael D. Vose, Alden H. Wright

It is supposed that the finite search space# has certain symmetries which can be described in terms of a group of permutations acting upon it. If crossover and mutation respect these symmetries then...

Tight bounds for blind search on the integers (2008)

Dietzfelbinger, Martin, Rowe, Jonathan E., Wegener, Ingo, Woelfel, Philipp

We analyze a simple random process in which a token is moved in the interval A = [0,n]: Fix a probability distribution µ over [1,n]. Initially, the token is placed in a random position in A. In...

22. Tight Bounds for Blind Search on the Integers (2008)

Dietzfelbinger, Martin, Rowe, Jonathan E., Wegener, Ingo, Woelfel, Philipp

We analyze a simple random process in which a token is moved in the interval $A={0,dots,n$: Fix a probability distribution $mu$ over ${1,dots,n$. Initially, the token is placed in a random position...

08051 Executive Summary -- Theory of Evolutionary Algorithms (2008)

Arnold, Dirk V., Auger, Anne, Rowe, Jonathan E., Witt, Carsten

The 2008 Dagstuhl Seminar "Theory of Evolutionary Algorithms" was the fifth in a firmly established series of biannual events. In the week from Jan. 27, 2008 to Feb. 1, 2008, 47 researchers from nine...

08051 Abstracts Collection -- Theory of Evolutionary Algorithms (2008)

Arnold, Dirk V., Auger, Anne, Witt, Carsten, Rowe, Jonathan E.

From Jan. 27, 2008 to Feb. 1, 2008, the Dagstuhl Seminar 08051 ``Theory of Evolutionary Algorithms'' was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the...

genetic (2007)

Nicholas Freitag Mcphee, Riccardo Poli, Jonathan E. Rowe

schema theory analysis of mutation size biases in

Abstract (2007)

Jonathan E. Rowe, Michael D. Vose, Alden H. Wright

It is supposed that the finite search space Ω has certain symmetries which can be described in terms of a group of permutations acting upon it. If crossover and mutation respect these symmetries...

linear (2007)

Nicholas Freitag Mcphee, Riccardo Poli, Jonathan E. Rowe

schema theory analysis of mutation size biases in genetic programming with

Markov Models for GP and Variable-length GAs with Homologous Crossover (2007)

Riccardo Poli, Jonathan E. Rowe, Nicholas Freitag Mcphee

In this paper we present a Markov model for GP and variable-length GAs with homologous crossover: a set of operators where the offspring are created preserving the position of the genetic material...

Continuous Dynamical System Models of Steady-State Genetic Algorithms (2007)

Alden Wright Computer, Alden H. Wright, Jonathan E. Rowe

This paper constructs discrete-time and continuous-time dynamical system expected value and infinite population models for steady-state genetic and evolutionary search algorithms. Conditions are...

How fast does the stationary distribution of the Markov chain modelling EAs concentrate on the homogeneous populations for small mutation rate? (2006)

Mitavskiy, Boris S., Rowe, Jonathan E.

The state space of the Markov chain modelling an evolutionary algorithm is quite large especially if the population space and the search space are large. I shell introduce an appropriate notion of...

06061 Executive Summary -- Theory of Evolutionary Algoritms (2006)

Arnold, Dirk V., Jansen, Thomas, Rowe, Jonathan E., Vose, Michael D.

The 2006 Dagstuhl Seminar ``Theory of Evolutionary Algorithms'' carried forward a series of Dagstuhl seminars that started in 2000 and has become an established event in the community. In the week...

06061 Abstracts Collection -- Theory of Evolutionary Algorithms (2006)

Arnold, Dirk V., Jansen, Thomas, Rowe, Jonathan E., Vose, Michael D.

From 05.02.06 to 10.02.06, the Dagstuhl Seminar 06061 ``Theory of Evolutionary Algorithms'' was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar,...

State aggregation and population dynamics in linear systems (2005)

Jonathan E. Rowe, Michael D. Vose, Alden H. Wright

Abstract We consider complex systems that are composed of many interacting elements, evolving under some dynamics. We are interested in characterizing the ways in which these elements may be grouped...

Coarse graining selection and mutation (2005)

Jonathan E. Rowe, Michaeld. Vose, Alden H. Wright

Abstract. Coarse graining is defined in terms of a commutative diagram. Necessary and sufficient conditions are given in the continuously differentiable case. The theory is applied to linear coarse...

Coarse graining selection and mutation (2005)

Jonathan E. Rowe, Michael D. Vose, Alden H. Wright

Abstract. Coarse graining is defined in terms of a commutative diagram. Necessary and sufficient conditions are given in the continuously differentiable case. The theory is applied to linear coarse...

An evolution strategy using a continuous version of the Gray-code neighbourhood distribution (2004)

Jonathan E. Rowe

Abstract. We derive a continuous probability distribution which generates neighbours of a point in an interval in a similar way to the bitwise mutation of a Gray code binary string. This distribution...

Structural search spaces and genetic operators (2004)

Jonathan E. Rowe, Michael D. Vose, Alden H. Wright

In a previous paper (Rowe et al., 2002), aspects of the theory of genetic algorithms were generalised to the case where the search space, Ω, had an arbitrary group action defined on it. Conditions...

Validating a model of colon colouration using an evolution strategy with adaptive approximations (2004)

Jonathan E Rowe

Abstract. The colour of colon tissue, which depends on the tissue structure, its optical properties, and the quantities of the pigments present in it, can be predicted by a physics-based model of...

Exact Schema Theory and Markov Chain Models for Genetic Programming and Variable-length Genetic Algorithms with Homologous Crossover (2004)

Riccardo Poli, Nicholas Freitag McPhee, Jonathan E. Rowe

Genetic Programming (GP) homologous crossovers are a group of operators, including GP onepoint crossover and GP uniform crossover, where the offspring are created preserving the position of the...

Bistability in a Gene Pool GA with Mutation (2003)

Alden H. Wright, Jonathan E. Rowe, Christopher R. Stephens, Riccardo Poli

It is possible for a GA to have two stable fixed points on a single-peak fitness landscape.

Implicit Parallelism (2003)

Michael Vose Alden, Michael D. Vose, Alden H. Wright, Jonathan E. Rowe

This paper describes the remarkable properties of structural crossover and mutation with respect to families of competing schemata. Recall that a schema defines certain components as taking on fixed...

Implicit parallelism (2003)

Michael D. Vose, Alden H. Wright, Jonathan E. Rowe

Abstract. This paper assumes a search space of fixed-length strings, where the size of the alphabet can vary from position to position. Structural crossover is mask-based crossover, and thus includes...

Implicit parallelism (2003)

Alden H. Wright, Michael D. Vose, Jonathan E. Rowe

Abstract. This paper assumes a search space of fixed-length strings, where the size of the alphabet can vary from position to position. Structural crossover is mask-based crossover, and thus includes...

Allele di#usion in linear genetic programming and variable-length genetic algorithms with subtree crossover (2002)

Riccardo Poli, Jonathan E. Rowe, Christopher R. Stephens, Alden H. Wright

In this paper we study, theoretically, the search biases produced by GP subtree crossover when applied to linear representations, such as those used in linear GP or in variable length GAs. The study...

On the search biases of homologous crossover in linear genetic programming and variable-length genetic algorithms (2002)

Riccardo Poli, Christopher R. Stephens, Ciencias Nucleares, Alden H. Wright, Jonathan E. Rowe

In this paper we study with a schema-theoretic approach and experiments the search biases produced by GP/GA homologous crossovers when applied to linear, variable-length representations. By...

Analysis of the simple genetic algorithm on the single-peak and double-peak landscapes (2002)

Alden H. Wright, Jonathan E. Rowe, James R. Neil

We compare the behavior of a GA with and without crossover. A simple GA with crossover can have two stable fixed points (bistability) on the single-peak landscapes for string lengths at least 8....

A Fixed Point Analysis of a Gene Pool GA with Mutation (2002)

Alden Wright Computer, Alden H. Wright, Riccardo Poli, Jonathan E. Rowe

This paper was written while Alden Wright was visiting the School of Computer Science, University of Birmingham, UK. linkage equilibrium. In a linkage equilibrium population, the representation of...

On the Search Biases of Homologous Crossover in Linear Genetic Programming and Variable-Length Genetic Algorithms (2002)

Riccardo Poli, Christopher R. Stephens, Alden H. Wright, Jonathan E. Rowe

With a schema-theoretic approach and experiments we study the search biases produced by GP/GA homologous crossovers when applied to linear, variable-length representations. By specialising the schema...

Bistability in a Gene Pool GA with Mutation (2002)

Alden Wright Computer, Alden H. Wright, Christopher R. Stephens, Jonathan E. Rowe, Riccardo Poli

It is possible for a GA to have two stable fixed points on a single-peak fitness landscape.

Allele Diffusion in Linear Genetic Programming and Variable-Length Genetic Algorithms with Subtree Crossover (2002)

Riccardo Poli, Jonathan E. Rowe, Christopher R. Stephens, Alden H. Wright

In this paper we study, theoretically, the search biases produced by GP subtree crossover when applied to linear representations, such as those used in linear GP or in variable length GAs. The study...

Great Britain (2002)

Alden H. Wright, Jonathan E. Rowe

This paper constructs discrete-time and continuous-time dynamical system expected value and infinite population models for steady-state genetic and evolutionary search algorithms. Conditions are...

A fixed point analysis of A gene pool GA with mutation (2002)

Alden H. Wright, Jonathan E. Rowe

This paper analyzes a recombination/mutation/selection genetic algorithm that uses gene pool recombination. For linear fitness functions, the infinite population model can be described by ℓ...

A normed space of genetic operators with applications to scalability issues (2001)

Jonathan E. Rowe

We define an abstract normed vector space where the genetic operators are elements. This is used to define the disturbance of the generational operator G as the distance between the crossover and...

A Fixed Point Analysis of a Gene Pool GA with Mutation (2001)

Alden H. Wright, Jonathan E. Rowe, Riccardo Poli, Christopher R. Stephens

This paper analyzes a recombination /mutation/selection genetic algorithm that uses gene pool recombination. For linear fitness functions, the infinite population model can be described by #...

Markov Chain Models for GP and Variable-length GAs with Homologous Crossover (2001)

Riccardo Poli, Jonathan E. Rowe, Nicholas Freitag McPhee

In this paper we present a Markov chain model for GP and variable-length GAs with homologous crossover: a set of GP operators where the offspring are created preserving the position of the genetic...

Abstract (2001)

Alden H. Wright, James R. Neil, Jonathan E. Rowe

We compare the behavior of a GA with and without crossover. A simple GA with crossover can have two stable fixed points (bistability) on the single-peak landscapes for string lengths at least 8....

Molecular circuits for associative learning in single-celled organisms

Fernando, Chrisantha T., Liekens, Anthony M.L., Bingle, Lewis E.H., Beck, Christian, Lenser, Thorsten, Stekel, Dov J., ...

We demonstrate how a single-celled organism could undertake associative learning. Although to date only one previous study has found experimental evidence for such learning, there is no reason in...