I am Professor of Artificial Intelligence and based in the Department of Computer Science at UWE. My research interests are in nature-inspired and unconventional systems, with an emphasis on evolution. I am the founding Editor-in-Chief of the Springer journal Evolutionary Intelligence.
UFCE3K-20-3 - Advances in Artificial Intelligence.
Previously module leader for:
UQC834HM - Artificial Life.
UQC833HM - Evolutionary Computation.
UFCE3N-15-M - Learning Classifier Systems.
UFCE3N-60-M - Computer Science Dissertation.
UFCE3K-20-3 - Machine Learning.
Previously programme leader for:
BSc Artificial Intelligence
MSc Machine Learning and Adaptive Computing
External Examiner:
University of Hertfordshire (2002-2005)
University of Bristol (2005-2009)
PhD Students
David Howard (current) - Spiking Neural Learning Classifier Systems
Richard Preen (current) - Dynamical Genetic Programming Learning Classifier Systems
Jeff Jones (current) - Multi-agent Modelling of Physarum polycephalum
Mehmet Erbas (current) - Imitation and Learning in Collective Robot Systems
Matt Smith (2009) - Using Genetic Programming for Feature Creation with a Genetic Algorithm Feature Selector
Andrea Staggemeier (2008) - Metaheuristics in a Production Lot-Sizing and Scheduling Problem
Johnson Abraham (2007) - Multi-objective Information Generation and Presentation within Interactive Evolutionary Design and Decision Making Systems
Toby O'Hara (2006) - Neural Representations in Learning Classifier Systems
Faten Kharbat (2006) - Learning Classifier Systems for Knowledge Discovery in Breast Cancer
Matt Studley (2005) - Learning Classifier Systems for Multi-objective Robot Control
Christopher Stone (2005) - Learning Classifier Systems for Decision Making in Continuous-Valued Domains
David Wyatt (2004) - Applying the XCS Learning Classifier System to Continuous-Valued Data Mining Problems
Claudio Bonacina (2003) - Evolutionary Computing in Multi-Agent Systems
Jacob Hurst (2002) - Learning Classifier Systems in Robotic Environments
Natalio Krasnogor (2002) - Studies on the Theory and Design Space of Memetic Algorithms
Manu Ahluwalia (2000) - Coevolving Functions in Genetic Programming
Andy Tomlinson (1999) - Corporate Classifier Systems
Publications
Coevolutionary Computation
Bull, L. (1995) Artificial Symbiology: evolution in cooperative multi-agent
environments. PhD Dissertation, UWE.
Bull, L. (ed)(1998) Coevolutionary Computation: Darwinian Multi-Agent Systems. Unpublished.
Fundamentals
Bull, L. (1997) Evolutionary Computing in Multi-Agent Environments: Partners.
In T.Baeck (ed) Proceedings of the Seventh International Conference
on Genetic Algorithms. Morgan Kaufmann, pp370-377.
Bull, L. (1998) Evolutionary Computing in Multi-Agent Environments: Operators.
In V.W. Porto, N. Saravanan, D. Wagen & A.E. Eiben (eds) Proceedings
of the Seventh Annual Conference on Evolutionary Programming. Springer
Verlag, pp43-52.
[j]
Bull, L. (2001) On Coevolutionary Genetic Algorithms. Soft Computing 5(3): 201-207.
Aickelin, U. & Bull, L. (2002) Partnering Strategies for Fitness Evaluation in a Pyramidal
Evolutionary Algorithm. In
W.B.Langdon, E.Cantu-Paz, K.Mathias, R. Roy, D.Davis, R. Poli,
K.Balakrishnan, V. Honavar, G. Rudolph, J. Wegener, L. Bull,
M. A. Potter, A.C. Schultz, J. F. Miller, E. Burke & N.Jonoska (eds) GECCO-2002:
Proceedings of the Genetic and Evolutionary Computation Conference. Morgan Kaufmann, pp263-270.
[j]
Aickelin, U. & Bull, L. (2003) On Hierarchical Coevolutionary Genetic Algorithms: Recombination and
Evaluation Partners. Applied System Sciences 4(2):2-17.
Macro-level Operators: Speciation, Symbiogenesis and Gene Sharing
Bull, L. & Fogarty, T.C. (1996) Evolutionary Computing in Cooperative
Multi-Agent Systems. In S. Sen (ed) Proceedings of the 1996 AAAI Symposium
on Adaptation, Coevolution and Learning in Multi-agent Systems. AAAI,
pp22-27.
Bull, L. & Fogarty, T.C. (1996) Evolutionary Computing in Multi-Agent
Environments: Speciation and Symbiogenesis. In H-M. Voigt, W. Ebeling,
I. Rechenberg & H-P. Schwefel (eds) Parallel Problem Solving from
Nature - PPSN IV. Springer Verlag, pp12-21.
[j]
Bull, L. (1999) On Evolving Social Systems.
Computational and Mathematical
Organization Theory 5(3):281-298.
Bull, L. (2005) Coevolutionary Species Adaptation Genetic Algorithms: Growth and Mutation on Coupled Fitness Landscapes. In Proceedings of the IEEE Congress on Evolutionary Computation. IEEE Press, pp559-564.
Bull, L. (2005) Coevolutionary Species Adaptation Genetic Algorithms: A Continuing SAGA on Coupled Fitness Landscapes. In M. Capcarrere et al. (eds) Proceedings of the Eighth European Conference on Artificial Life. Springer, pp322-331.
Homogeneous Systems: Collective Agents and Cellular Automata
Bull, L. & Holland, O. (1997) Evolutionary Computing in Multi-Agent
Environments: Eusociality. In J.R. Koza, K. Deb, M. Dorigo, D.B. Fogel,
M. Garzon, H. Iba & R.L. Riolo (eds)
Proceedings of the Second Annual
Conference on Genetic Programming. Morgan Kaufmann, pp347-352.
[j]
Bull, L. (2003) Simple Models of Coevolutionary Genetic Algorithms. Artificial
Life and Robotics 5(1):58-65.
Sapin, E., & Bull, L. (2007) Searching for Glider Guns in Cellular Automata: Exploring Evolutionary and Other Techniques. In N. Monmarche et al. (eds) Artificial Evolution: Proceedings of the 8th International Conference on Evolution Artificielle. Springer, pp255-265.
Sapin, E., Bull, L. & Adamatzky, A. (2007) A Genetic Approach to Search for Glider Guns in Cellular Automata. In Proceedings of the IEEE Congress on Evolutionary Computation. IEEE Press, pp2456-2462.
[j]
Adamatzky, A., Bull, L., Collet, P. & Sapin, E. (2008) Evolving Localizations in Reaction-Diffusion Cellular Automata. International Journal of Modern Physics C 19(4): 557-567.
[j]
Sapin, E. & Bull, L. (2008) Evolutionary Search for Cellular Automata Logic Gates with Collision-based Computing. Complex Systems 17(4): 321-338.
[j]
Sapin, E., Bull, L. & Adamatzky, A. (2009) Genetic Approaches to Search for Computing Patterns in Cellular
Automata. IEEE Computational Intelligence Magazine 4(3): 20-28.
[j]Stone, C. & Bull, L. (2009) Evolution of Cellular Automata with Memory: The Density Classification Task. BioSystems 97(2): 108-116.
[j]
Sapin, E., Collet, P., Adamatzky, A. & Bull, L. (2010) Stochastic Automated Search Methods in Cellular Automata: The Discovery of Tens of Thousands Glider Guns. Natural Computing (in press).
Genetic Programming: Automatic Function Specification (Speciation)
Ahluwalia, M., Bull, L. & Fogarty, T.C. (1997) Coevolving Functions
in Genetic Programming: A Comparison in ADF Selection Strategies. In J.R.
Koza, K. Deb, M. Dorigo, D.B. Fogel, M. Garzon, H. Iba & R.L. Riolo
(eds) Proceedings of the Second Annual Conference on Genetic Programming.
Morgan Kaufmann, pp3-8.
Ahluwalia, M., Bull, L. & Fogarty, T.C. (1997) Coevolving Functions
in Genetic Programming: An Emergent Approach using ADFs and GLiB. In J.R.
Koza (ed)
Late Breaking Papers at the Genetic Programming 1997 Conference.
Stanford University, pp1-6.
Ahluwalia, M. & Bull, L. (1998) Coevolving Functions in Genetic Programming:
Dynamic ADF Creation using GLiB. In V.W. Porto, N. Saravanan, D. Wagen
& A.E. Eiben (eds) Proceedings of the Seventh Annual Conference
on Evolutionary Programming. Springer Verlag, pp809-818.
Ahluwalia, M. & Bull, L. (1999) Coevolving Functions in Genetic Programming:
Classification using K-nearest-neighbour. In W. Banzhaf, J. Daida, A.E.
Eiben, M.H. Garzon, V. Honavar, M. Jakiela & R.E. Smith (eds)
GECCO-99:
Proceedings of the Genetic and Evolutionary Computation Conference.
Morgan Kaufmann, pp947-952.
[j]
Ahluwalia, M. & Bull, L. (2001) Coevolving Functions in Genetic Programming.
Systems Architecture 47: 573-585.
W.B.Langdon, E.Cantu-Paz, K.Mathias, R. Roy, D.Davis, R. Poli,
K.Balakrishnan, V. Honavar, G. Rudolph, J. Wegener, L. Bull,
M. A. Potter, A.C. Schultz, J. F. Miller, E. Burke & N.Jonoska (eds)(2002) GECCO-2002:
Proceedings of the Genetic and Evolutionary Computation Conference. Morgan Kaufmann.(Founded LCS track)
Bull, L., Lanzi, P-L. & Stolzmann, W. (eds)(2002) Soft Computing: Special Issue on Learning Classifier
Systems 6(3-4). Springer.
Bull, L. & Lanzi, P-L. (eds)(2009) Natural Computing: Special Issue on Learning Classifier
Systems 8(1). Springer.
Fundamentals
Bull, L. (2001) Simple Markov Models of the Genetic Algorithm in Classifier Systems: Multi-Step Tasks.
In P-L. Lanzi, W. Stolzmann &
S.W. Wilson (eds) Advances in Learning Classifier Systems:
Proceedings of the Third International Workshop. Springer, pp29-36.
Bull, L. (2001) Simple Markov Models of the Genetic Algorithm in Classifier Systems: Accuracy-Based Fitness.
In P-L. Lanzi, W. Stolzmann &
S.W. Wilson (eds) Advances in Learning Classifier Systems:
Proceedings of the Third International Workshop. Springer, pp21-28.
[j]
Bull, L. (2002) On Accuracy-Based Fitness. Soft Computing 6(3-4): 154-161.
[j]
Bull, L. & Hurst, J. (2002) ZCS Redux. Evolutionary Computation 10(2): 185-205.
Bull, L., Wyatt, D. & Parmee, I. (2002) Initial Modifications to XCS for use in Interactive Evolutionary Design.
In J. Merelo, P. Adamidis, H-G. Beyer, J-L. Fernandez-Villacanas & H-P. Schwefel (eds)
Parallel Problem Solving from Nature - PPSN VII, Springer Verlag, pp568-577.
Hurst, J., Bull, L. & Melhuish, C. (2002) TCS Learning Classifier System Controller on a Real Robot.
In J. Merelo, P. Adamidis, H-G. Beyer, J-L. Fernandez-Villacanas & H-P. Schwefel (eds) Parallel
Problem Solving from Nature - PPSN VII. Springer Verlag, pp588-600.
Bull, L. (2004) A Simple Payoff-based Learning Classifier System.
In X. Yao et al. (eds) Parallel Problem Solving from Nature - PPSN VIII. Springer Verlag, pp1032-1041.
Kharbat, F., Bull, L. & Odeh, M. (2004) Further Investigation of Accuracy-based Fitness Using a Simple Learning System. In Proceedings of the International Arab Conference on Information Technology (ACIT2004), pp311-318.
[b]Wyatt, D. & Bull, L. (2004) A Memetic Learning Classifier System for Describing Continuous-Valued Problem Spaces. In N. Krasnagor, W. Hart & J. Smith (eds) Recent Advances in Memetic Algorithms. Springer, pp355-396.
[b]
Bull, L. (2005) Two Simple Learning Classifier Systems. In
L. Bull & T. Kovacs (eds) Foundations of Learning Classifier Systems. Springer, pp63-90.
Kharbat, F., Bull, L. & Odeh, M. (2005) Revisiting Genetic Selection in the XCS Learning Classifier System. In Proceedings of the IEEE Congress on Evolutionary Computation. IEEE, pp2061-2068.
Studley, M. & Bull, L. (2005) X-TCS: Accuracy-based Learning Classifier System Robotics. In Proceedings of the IEEE Congress on Evolutionary Computation. IEEE, pp2099-2106.
[j]
Kharbat, F., Odeh, M. & Bull, L. (2007) New Approach for Extracting Knowledge from XCS Learning Classifier Systems. International Journal of Hybrid Intelligent Systems 4(2): 49-62.
Kovacs, T. & Bull, L. (2007) Toward a Better Understanding of Rule Initialisation and Deletion. In Proceedings of the Genetic and Evolutionary Computation Conference
Workshop Program. ACM Press, pp2777-2780.
Unsupervised Learning: Clustering
Tammee, K., Bull, L. & Ouen, P. (2006) A Learning Classifier System Approach to Clustering. In Proceedings of the 6th International Conference on Intelligent Systems Design and Applications. IEEE, pp621-626.
Tammee, K., Bull, L. & Ouen, P. (2006) Using a Learning Classifier System for Clustering. In Proceedings of the International Symposium on Communications and Information Technologies 2006. IEEE.
[j]
Tammee, K., Bull, L. & Ouen, P. (2007) YCSc: A Modified Clustering Technique based on LCS. Journal of Digital Information Management 5(3): 160-167.
Tammee, K., Bull, L. & Ouen, P. (2007) Towards Clustering with XCS. In D. Thierens et al. (eds) GECOO-2007: Proceedings of the Genetic and Evolutionary Computation Conference. ACM Press, pp1854-1860.
[b]
Tammee, K., Bull, L. & Ouen, P. (2008) Towards Clustering with Learning Classifier Systems. In L. Bull, E. Bernado-Mansilla & J. Holmes (eds) Learning Classifier Systems in Data Mining. Springer, pp191-204.
Cognition: Memory, Lookahead, Latent Learning, and Multiple Objectives
Bull, L. & Holland, O. (1994) Internal and External Representations:
A Comparison in Evolving the Ability to Count. In Proceedings of the
First Annual Society for the Study of Artificial Intelligence and Simulated
Behaviour Robotics Workshop. AISB, pp11-14.
Bull, L. (2002) Lookahead and Latent Learning in ZCS. In
W.B.Langdon, E.Cantu-Paz, K.Mathias, R. Roy, D.Davis, R. Poli,
K.Balakrishnan, V. Honavar, G. Rudolph, J. Wegener, L. Bull,
M. A. Potter, A.C. Schultz, J. F. Miller, E. Burke & N.Jonoska (eds) GECCO-2002:
Proceedings of the Genetic and Evolutionary Computation Conference. Morgan Kaufmann, pp897-904.
Bull, L. (2004) Lookahead and Latent Learning in a Simple Accuracy-based Learning Classifier System.
In X. Yao et al. (eds) Parallel Problem Solving from Nature - PPSN VIII. Springer Verlag, pp1042-1050.
[b]
Bull, L., Sha'Aban, J., Tomlinson, A., Addison, P. & Heydecker, B. (2004) Towards Distributed Adaptive Control for Road Traffic Junction Signals using Learning Classifier Systems. In L. Bull (ed) Applications of Learning Classifier Systems. Springer, pp276-299.
O'Hara, T. & Bull, L. (2005) Building Anticipations in an Accuracy-based Learning Classifier System by use of an Artificial Neural Network. In Proceedings of the IEEE Congress on Evolutionary Computation. IEEE Press, pp2046-2052.
[j]
Studley, M. & Bull, L. (2006) Using the XCS Classifier System for Multi-objective Reinforcement Learning Problems. Artificial Life 13(1): 69-86.
Bull, L., Lanzi, P-L. & O'Hara, T. (2007) Anticipation Mappings for Learning Classifier Systems. In Proceedings of the IEEE Congress on Evolutionary Computation. IEEE Press, pp2133-2140.
Bull, L. (2008) On Lookahead and Latent Learning in Simple LCS. In J. Bacardit, et al. (eds) Learning Classifier Systems: Proceedings of the International Workshops IWLCS 2006 and 2007. Springer, pp154-168.
Corporations: Rule-Linkage
Tomlinson, A. & Bull, L. (1998) A Corporate Classifier System. In A.E.
Eiben, T. Baeck, M. Schoenauer & H-P. Schwefel (eds) Parallel Problem
Solving from Nature - PPSN V. Springer Verlag, pp550-559.
Tomlinson, A. & Bull, L. (1999) On Corporate Classifier Systems: Improving
the use of Rule-Linkage. In W. Banzhaf, J. Daida, A.E. Eiben, M.H. Garzon,
V. Honavar, M. Jakiela & R.E. Smith (eds)
GECCO-99: Proceedings
of the Genetic and Evolutionary Computation Conference. Morgan Kaufmann,
pp649-656.
Tomlinson, A. & Bull, L. (1999) A Zeroth Level Corporate Classifier
System. In A.S. Wu (ed)
Proceedings of the Genetic and Evolutionary Computation Conference
Workshop Program. Gecco, pp306-313.
[b]
Tomlinson, A. & Bull, L. (2000) A Corporate XCS. In P-L. Lanzi, W. Stolzmann &
S.W. Wilson (eds) Learning Classifier Systems: From Foundations to Applications, Springer, pp194-208.
[j]
Tomlinson, A. & Bull, L. (2001) Symbiogenesis in Learning Classifier Systems. Artificial Life 7(1):33-62.
Tomlinson, A. & Bull, L. (2001) CXCS: Improvements and Corporate Generalizations.
In L. Spector et al. (eds) GECCO-2001: Proceedings
of the Genetic and Evolutionary Computation Conference. Morgan Kaufmann, pp966-973.
[j]
Tomlinson, A. & Bull, L. (2002) An Accuracy-Based Corporate Classifier System. Soft Computing 6(3-4): 200-215.
Multi-Agent Systems: Pittsburgh-style, Communication and Rule Sharing
Bull, L. & Fogarty, T.C. (1993) Coevolving Communicating Classifier
Systems for Tracking. In R.F. Albrecht, C.R. Reeves & N.C. Steele (eds)
Artificial
Neural Networks and Genetic Algorithms. Springer Verlag, pp522-527.
Bull, L. & Fogarty, T.C. (1994) Evolving Cooperative Communicating
Classifier Systems. In A.V. Sebald & L.J. Fogel (eds) Proceedings
of the Third Annual Conference on Evolutionary Programming. World Scientific,
pp308-315.
Bull, L. & Fogarty, T.C. (1994) Parallel Evolution of Communicating
Classifier Systems. In Proceedings of the 1994 IEEE Conference on Evolutionary
Computing. IEEE, pp680-685.
Bull, L., Fogarty T.C. & Snaith, M. (1995) Evolution in Multi-Agent
Systems: Evolving Communicating Classifier Systems for Gait in a Quadrupedal
Robot. In L.J. Eshelman (ed) Proceedings of the Sixth International
Conference on Genetic Algorithms. Morgan Kaufmann, pp382-388.
Bull, L., Fogarty, T.C., Mikami, S., & Thomas, J.G. (1995) Adaptive
Gait Acquisition using Multi-agent Learning for Wall Climbing Robots. In
Automation
and Robotics in Construction XII. IMBibg, pp80-86.
[j]
Fogarty, T.C. & Bull, L. (1995) Optimising Individual Control Rules
and Multiple Communicating Rule-based Control Systems with Parallel Distributed
Genetic Algorithms. IEE Journal of Control Theory and Applications
142(3): 211-215.
[b]
Fogarty, T.C., Bull, L. & Carse, B. (1995) Evolving Multi-Agent Systems.
In J. Periaux & G. Winter (eds) Genetic Algorithms in Engineering
and Computer Science. John Wiley & Sons, pp3-22.
[j]
Fogarty, T.C., Carse, B. & Bull, L. (1994) Classifier Systems - recent
research. AISB Quarterly (89):48-54.
Fogarty, T.C., Carse, B. & Bull, L. (1995) Classifier Systems: selectionist
reinforcement learning, fuzzy rules and communication. In Proceedings
of the First International Workshop on Biologically Inspired Evolutionary
Systems.
[b]
Fogarty, T.C., Ireson, N.S. & Bull, L. (1995) Genetic-based Machine
Learning - Applications in Industry and Commerce. In V.J. Rayward-Smith
(ed) Applications of Modern Heuristic Methods. Alfred Waller Ltd,
pp91-110.
Bull, L. (1998) On ZCS in Multi-Agent Environments. In A.E. Eiben, T. Baeck,
M. Schoenauer & H-P. Schwefel (eds) Parallel Problem Solving from
Nature - PPSN V. Springer Verlag, pp471-480.
Bull, L. (1999) On using ZCS in a Simulated Continuous Double-Auction Market.
In W. Banzhaf, J. Daida, A.E. Eiben, M.H. Garzon, V. Honavar, M. Jakiela
& R.E. Smith (eds)
GECCO-99: Proceedings of the Genetic and Evolutionary
Computation Conference. Morgan Kaufmann, pp83-90.
Cao, Y.J., Ireson, N., Bull, L. & Miles, R. (2000) Distributed Learning
Control of Traffic Signals. In S. Cagnoni, R. Poli, G. Smith, D. Corne, M. Oates,
E. Hart, P-L. Lanzi, E. Willem, Y. Li, B. Paecther & T.C. Fogarty (eds)
Real-World Applications of Evolutionary Computing: Proceedings of the EvoNet
Workshops - EvoSCONDI 2000. Springer, pp117-126.
Ireson, N., Cao. Y.J, Bull, L. & Miles, R. (2000) A Communication Architecture
for Multi-Agent Learning Systems. In S. Cagnoni, R. Poli, G. Smith, D. Corne, M. Oates,
E. Hart, P-L. Lanzi, E. Willem, Y. Li, B. Paecther & T.C. Fogarty (eds)
Real-World Applications of Evolutionary Computing: Proceedings of the EvoNet Workshops
- EvoTel 2000. Springer, pp255-266.
[j]
Cao, Y.J., Ireson, N., Bull, L. & Miles, R. (2001) An Evolutionary Intelligent Agents Approach to
Traffic Signal Control. International Journal of Knowledge-based Intelligent Engineering Systems 5(4):279-289.
Bull, L., Studley, M., Bagnall, A. & Whittley, I. (2005) On the use of Rule Sharing in Learning Classifier System Ensembles. In Proceedings of the IEEE Congress on Evolutionary Computation. IEEE, pp612-617.
[j]
Bull, L., Studley, M., Bagnall, A. & Whittley, I. (2007) Learning Classifier System Ensembles with Rule Sharing. IEEE Transactions on Evolutionary Computation 11(4): 496-502
Self-Adaptation
Bull, L. & Hurst, J. (2000) Self-Adaptive Mutation in ZCS Controllers.
In S. Cagnoni, R. Poli, G. Smith, D. Corne, M. Oates,
E. Hart, P-L. Lanzi, E. Willem, Y. Li, B. Paecther & T.C. Fogarty (eds)
Proceedings of the EvoNet Workshops: EvoRob. Springer, pp339-346.
Bull, L. Hurst, J. & Tomlinson, A. (2000) Self-Adaptive Mutation in
Classifier System Controllers. In J-A. Meyer, A. Berthoz, D. Floreano,
H. Roitblatt & S.W. Wilson (eds) From Animals to Animats 6 - The
Sixth International Conference on the Simulation of Adaptive Behaviour.
MIT Press, pp460-468.
Hurst, J. & Bull, L. (2001) A Self-Adaptive Classifier System. In P-L. Lanzi, W. Stolzmann &
S.W. Wilson (eds) Advances in Learning Classifier Systems:
Proceedings of the Third International Workshop. Springer, pp70-79.
Hurst, J. & Bull, L. (2002) A Self-Adaptive XCS. In P-L. Lanzi, W. Stolzmann &
S.W. Wilson (eds) Advances in Learning Classifier Systems: Proceedings of the Fourth International
Workshop on Learning Classifier Systems. Springer, pp57-73.
[j]
Hurst, J. & Bull, L. (2003) Self-Adaptation in Classifier System Controllers. Artificial Life and Robotics 5(2): 109-119.
Real-Valued Representations: Intervals and Fuzzy Logic
Cao, Y.J., Ireson, N., Bull, L. & Miles, R. (1999) Design of a Traffic
Junction Controller using a Classifier System and Fuzzy Logic. In B. Reusch
(ed) Proceedings of the Sixth International Conference on Computational
Intelligence Theory and Applications. Springer Verlag, pp342-351.
Bull, L., Wyatt, D. & Parmee, I. (2002) Towards the use of XCS for Interactive Evolutionary Design. In
W.B.Langdon, E.Cantu-Paz, K.Mathias, R. Roy, D.Davis, R. Poli,
K.Balakrishnan, V. Honavar, G. Rudolph, J. Wegener, L. Bull,
M. A. Potter, A.C. Schultz, J. F. Miller, E. Burke & N.Jonoska (eds)
GECCO-2002:
Proceedings of the Genetic and Evolutionary Computation Conference. Morgan Kaufmann, pp951.
Stone, C. & Bull, L. (2003) Towards Learning Classifier Systems for Continuous-Valued Online Environments.
In GECCO-2003:
Proceedings of the Genetic and Evolutionary Computation Conference. Springer, pp1924-1925.
[j]
Stone, C. & Bull, L. (2003) For Real! XCS with Continuous-Valued Inputs. Evolutionary
Computation 11(3): 299-336.
Casillas, J. Carse, B. & Bull, L. (2004) Fuzzy XCS: an Accuracy-based Fuzzy Classifier System. In Proceedings of the XII Congreso Espanol sobre Tecnologia y Logica Fuzzy (ESTYLF 2004).
Wyatt, D., Bull, L. & Parmee, I. (2004) Building Compact Rulesets for Describing Continuous-Valued Problem Spaces Using a Learning Classifier System. In I. Parmee (ed) Adaptive Computing in Design and Manufacture VI. Springer, pp235-248.
[b] Stone, C. & Bull, L. (2005) An Analysis of Continuous-Valued Representations for Learning Classifier Systems. In
L. Bull & T. Kovacs (eds) Foundations of Learning Classifier Systems. Springer, pp127-178.
[j]Casillas, J. Carse, B. & Bull, L. (2007) Fuzzy XCS: a Michigan Genetic Fuzzy System. IEEE Transactions on Fuzzy Systems 15(4): 536-550.
Kharbat, F., Bull, L. & Odeh, M. (2007) Mining Breast Cancer Data with XCS. In D. Thierens et al. (eds) GECOO-2007: Proceedings of the Genetic and Evolutionary Computation Conference. ACM Press, pp2066-2073.
Wyatt, D., Bull, L. & Parmee, I. (2007) Applying XCSR to Design-Orientated Environments. In T. Kovacs, X. Llora, K. Takadama, P-L. Lanzi, W. Stolzmann & S.W. Wilson (eds) Learning Classifier Systems: International Workshops IWLCS 2003-2005. Springer, pp318-342.
[b]
Kharbat, F., Bull, L. & Odeh, M. (2008) Knowledge Discovery from Medical Data: An Empirical Study with XCS. In L. Bull, E. Bernado-Mansilla & J. Holmes (eds) Learning Classifier Systems in Data Mining. Springer, pp93-122.
[b]
Stone, C. & Bull, L. (2008) Foreign Exchange Trading using a Learning Classifier System. In L. Bull, E. Bernado-Mansilla & J. Holmes (eds) Learning Classifier Systems in Data Mining. Springer, pp169-190.
Genetic Programming
Ahluwalia, M. & Bull, L. (1999) A Genetic Programming-based Classifier
System. In W. Banzhaf, J. Daida, A.E. Eiben, M.H. Garzon, V. Honavar, M.
Jakiela & R.E. Smith (eds)
GECCO-99: Proceedings of the Genetic
and Evolutionary Computation Conference. Morgan Kaufmann, pp11-18.
[j]
Bull, L. (2009) On Dynamical Genetic Programming: Simple Boolean Networks in Learning Classifier
Systems.
International Journal of Parallel, Emergent and Distributed Systems 24(5): 421-442
Bull, L. & Preen, R. (2009) On Dynamical Genetic Programming: Random Boolean Networks in Learning Classifier
Systems. In L. Vanneschi et al. (eds) Proceedings of the Twelfth European Conference on Genetic Programming. Springer, pp37-48.
Preen, R. & Bull, L. (2009) Discrete Dynamical Genetic Programming in XCS. In GECCO-2009: Proceedings of the Genetic and Evolutionary Computation Conference. ACM Press.
Neural Learning Classifier Systems
Bull, L. (2002) On Using Constructivism in Neural Classifier Systems.
In J. Merelo, P. Adamidis, H-G. Beyer, J-L. Fernandez-Villacanas & H-P. Schwefel (eds)
Parallel Problem Solving from Nature - PPSN VII. Springer Verlag, pp558-567.
Bull, L. & O'Hara, T. (2002) Accuracy-based Neuro and Neuro-Fuzzy Classifier Systems. In
W.B.Langdon, E.Cantu-Paz, K.Mathias, R. Roy, D.Davis, R. Poli,
K.Balakrishnan, V. Honavar, G. Rudolph, J. Wegener, L. Bull,
M. A. Potter, A.C. Schultz, J. F. Miller, E. Burke & N.Jonoska (eds)
GECCO-2002: Proceedings of the Genetic and Evolutionary Computation Conference.
Morgan Kaufmann, pp905-911.
Bull, L. & Studley, M. (2002)
Consideration of Multiple Objectives in Neural Learning Classifier Systems.
In J. Merelo, P. Adamidis, H-G. Beyer, J-L. Fernandez-Villacanas & H-P. Schwefel (eds)
Parallel Problem Solving from Nature - PPSN VII. Springer Verlag, pp549-557.
Bull, L. & Hurst, J. (2003)
A Neural Learning Classifier System with Self-Adaptive Constructivism. In
Proceedings of the IEEE Congress on Evolutionary Computation. IEEE Press, pp991-997.
Hurst, J. & Bull, L. (2004) A Self-Adaptive Neural Learning Classifier System with Constructivism for Mobile Robot Control.
In X. Yao et al. (eds) Parallel Problem Solving from Nature - PPSN VIII. Springer Verlag, pp942-951.
O'Hara, T. & Bull, L. (2005) A Memetic Accuracy-based Neural Learning Classifier System. In Proceedings of the IEEE Congress on Evolutionary Computation. IEEE Press, pp2040-2045.
[j]
Hurst, J. & Bull, L. (2006) A Neural Learning Classifier System with Self-Adaptive Constructivism for Mobile Robot Control. Artificial Life 12(3): 353-380.
O'Hara, T. & Bull, L. (2007) Backpropagation in Accuracy-based Neural Learning Classifier Systems. In T. Kovacs, X. Llora, K. Takadama, P-L. Lanzi, W. Stolzmann & S.W. Wilson (eds) Learning Classifier Systems: International Workshops IWLCS 2003-2005. Springer, pp26-40.
Howard, D., Bull, L. & Lanzi, P-L. (2008) Self-Adaptive Constructivism in Neural XCS and XCSF. In M. Keijzer et al. (eds)
GECCO-2008: Proceedings of the Genetic and Evolutionary Computation Conference. ACM Press, pp1389-1396.
Howard, D. & Bull, L. (2008) On the Effects of Node Duplication and Connection-Orientated Constructivism in Neural XCSF. In M. Keijzer et al. (eds)
GECCO-2008: Proceedings of the Genetic and Evolutionary Computation Conference. ACM Press, pp1977-1984.
Howard, D., Bull, L. & Lanzi, P-L. (2009) Continuous Actions in Continuous Space and Time using Self-Adaptive Constructivism in Neural XCSF. In GECCO-2009: Proceedings of the Genetic and Evolutionary Computation Conference. ACM Press.
[j] Bull, L. (1996) Artificial Life: An Overview, by C.G. Langton. Expert
Systems 13(1):63
Adamatzky, A., Bull, L., De Lacy Costello, B.,Stepney, S. & Teuscher, C. (eds)(2007) Unconventional Computing 2007. Luniver Press.
Artificial Creativity: Interactive Evolutionary Computation, Fitness Modelling, and Variable-Dimension Search
Bull, L. (1997) Model-based Evolutionary Computing: A Neural Network and
Genetic Algorithm Architecture. In Proceedings of the 1997 IEEE Conference
on Evolutionary Computing. IEEE, pp611-616.
[j]
Bull, L. (1999) On Model-based Evolutionary Computing. Soft Computing
3(2):183-190.
Bull, L. (2008) Toward Artificial Creativity with Evolution Strategies. In I. Parmee (ed) Adaptive Computing in Design and Manufacture VIII. IPCC.
Baldwin Effect: Evolution, Learning, and Imitation
Bull, L. & Fogarty, T.C. (1994) An Evolution Strategy and Genetic Algorithm
Hybrid: An Initial Implementation and First Results. In T.C. Fogarty (ed)
Evolutionary
Computing. Springer Verlag, pp95-102.
Bull, L. (1997) On the Evolution of Multicellularity. In P. Husbands &
I. Harvey (eds) Proceedings of the Fourth European Conference on Artificial
Life. MIT Press, pp190-196.
[j]
Bull, L. (1999) On the Evolution of Multicellularity and Eusociality. Artificial
Life 5(1):1-15.
[j]
Bull, L. (1999) On the Baldwin Effect. Artificial Life 5(3):241-246.
[j]
Bull, L., Holland, O. & Blackmore,
S.(2000) On Meme-Gene Coevolution. Artificial Life 6(3): 227-235.
Discrete Dynamical Systems: Identification, Memory, and Coupling (see also here )
Bull, L., Lawson, I., Adamatzky, A. & DeLacyCostello, B. (2005) Towards Predicting Spatial Complexity: A Learning Classifier System Approach to Cellular Automata Identification. In Proceedings of the IEEE Congress on Evolutionary Computation. IEEE, pp136-141.
[j]
Bull, L. & Adamatzky (2007) A Learning Classifier System Approach to the Identification of Cellular Automata. Cellular Automata 2(1): 21-38.
[j]
Alonso-Sanz, R. & Bull, L. (2008) Random Number Generation by Cellular Automata with Memory. International Journal of Modern Physics C 19(2): 351-367.
Alonso-Sanz, R. & Bull, L. (2008) Elementary Coupled Cellular Automata with Memory. In Adamatzky et al. (eds) Automata 2008: Theory and Applications of Cellular Automata. Luniver Press, pp72-96.
[j]
Alonso-Sanz, R. & Bull, L. (2008) Boolean Networks with Memory. Bifurcation and Chaos 18(12): 3799-3814
Bull, L. & Alonso-Sanz, R. (2008) On Coupling Random Boolean Networks. In Adamatzky et al. (eds) Automata 2008: Theory and Applications of Cellular Automata. Luniver Press, pp292-301.
[j]
Alonso-Sanz, R. & Bull, L. (2009) On Minimally Coupled Boolean Networks. Bifurcation and Chaos 19(4): 1401-1414
[j]
Alonso-Sanz, R. & Bull, L. (2009) A Very Effective Density Classifier Two-Dimensional Cellular Automaton with Memory. Journal of Physics A 42(48):
[j]
Alonso-Sanz, R. & Bull, L. (2010) One-Dimensional Coupled Cellular Automata with Memory: Initial Investigations. Cellular Automata (in press)
[j]
Alonso-Sanz, R. & Bull, L. (2010) Elementary Cellular Automata with Minimal Memory and Random Number Generation. Complex Systems (in press)
[j]Stone, C. & Bull, L. (2010) Solving the Density Classification Task with Cellular Automaton 184 and Memory. Complex Systems (in press).
Symbiogenesis
Bull, L., Fogarty, T.C. & Pipe, A.G. (1995) Artificial Endosymbiosis.
In F. Moran, A. Mereno, J.J. Merelo & P. Chaon (eds) Advances in
Artificial Life - Proceedings of the Third European Conference on Artificial
Life. Springer Verlag, pp273-289.
Bull, L. & Fogarty, T.C. (1996) Horizontal Gene Transfer in Endosymbiosis.
In C.G. Langton & T. Shimohara (eds) Artificial Life V. MIT
Press, pp77-84.
[j]
Bull, L. & Fogarty, T.C. (1996) Artificial Symbiogenesis. Artificial
Life 2(3):269-292.
[b]
Bull, L. (1999) On the Evolution of Eukaryotes: Computational Models of
Symbiogenesis and Multicellularity. In C. Nehaniv (ed) Mathematical
and Computational Biology: Hierarchical Complexity and Digital Evolution.
American Mathematical Society, pp31-46.
[b]
Bull, L. & Tomlinson, A. (2004) Symbiogenesis in Machine Learning. In R. Paton (ed)
Computation in Cells and Tissues: Perspectives and Tools of Thought. Springer, pp27-50.
[j]
Bull, L. (2010) Artificial Symbiogenesis and Differing Reproduction Rates. Artificial
Life (in press).
Chemical Computation
Budd, A., Stone, C., Masere, J., Adamatzky, A., DeLacyCostello, B. & Bull, L. (2006) Towards Machine Learning Control of Chemical Computers. In A. Adamatzky & C. Teuscher (eds) From Utopian to Genuine Unconventional Computers. Luniver Press, pp17-36.
Stone, C., Toth, R., Adamatzky, A., Bull, L. & De Lacy Costello, B. (2007) Towards the Coevolution of Cellular Automata Controllers for Chemical Computing with the B-Z Reaction. In D. Thierens et al. (eds) GECOO-2007: Proceedings of the Genetic and Evolutionary Computation Conference. ACM Press, pp472-478.
[j]
Budd, A., Stone, C., Masere, J., Adamatzky, A., DeLacyCostello, B. & Bull, L. (2008) Initial Results from the use of Evolutionary Learning to Control Chemical Computers. Unconventional Computing 4(1): 13-22.
Stone, C., Toth, R., De Lacy Costello, B., Adamatzky, A. & Bull, L. (2008) Coevolving Cellular Automata with Memory for Chemical Computing: Boolean Logic Gates in the B-Z Reaction. In G. Rudolph et al. (eds) Parallel Problem Solving from Nature - PPSN X. Springer, pp579-588.
[j]
Taylor, A., Kapetanopoulos, P., Whitaker, B., Toth, R., Bull, L. & Tinsley, M. (2008) Clusters and Switchers in Globally Coupled Photochemical Oscillators. Physical Review Letters 100(21)
Toth, R., Stone, C., De Lacy Costello, B., Adamatzky, A. & Bull, L. (2008) Towards Designing Collision-based Chemical Logic Gates with Adaptive Computing. In I. Parmee (ed) Adaptive Computing in Design and Manufacture VIII. IPCC.
[j] Toth, R., Stone, C., De Lacy Costello, B., Adamatzky, A. & Bull, L. (2008) Dynamic Control and Information Processing in the Belousov-Zhabotinsky Reaction using a Co-evolutionary Algorithm. Journal of Chemical Physics 129: 184708.
[j]
Adamatzky, A. & Bull, L. (2009) Are Complex Systems Hard to Evolve? Complexity 14(6): 15-20.
[j] De Lacy Costello, B., Toth, R., Stone, C., Adamatzky, A. & Bull, L. (2009) Implementation of Glider Guns in the Light-Sensitive Belousov-Zhabotinsky Medium. Physical Review E 79(2).
[j] Toth, R., Stone, C., De Lacy Costello, B., Adamatzky, A. & Bull, L. (2009) Experimental validation of binary collisions between wave fragments in the photosensitive Belousov-Zhabotinsky reaction. Chaos, Solitons & Fractals 41(4): 1605-1615.
[j] Toth, R., Stone, C., De Lacy Costello, B., Adamatzky, A. & Bull, L. (2009) Simple Collision-based Chemical Logic Gates with Adaptive Computing. Journal of Nanotechnology and Molecular Computation 1(3): 1-16.
[j] Toth, R., De Lacy Costello, B., Stone, C., Adamatzky, A. & Bull, L. (2010) Spiral Formation and Degeneration in Heterogeneous Excitable Media. Physical Review E (in press).
Neuronal Computation
Uroukov, I., Ma, M., Bull, L. & Purcell, W. (2006) MEA Recordings of the Spontaneous Behaviour of Hen Embryo Brain Spheroids. In Proceedings of the 5th International Meeting on Substrate-Integrated Micro Electrode Arrays. BIOPRO, pp232-234.
[j]
Uroukov, I., Ma, M., Bull, L. & Purcell, W. (2006) Electrophysiological Measurements in 3-Dimensional In Vivo-Mimetic Organotypic Cell Cultures: Preliminary Studies with Hen Embryo Brain Spheroids. Neuroscience Letters 404: 33-38
Bull, L. & Uroukov, I. (2007) Initial Results from the use of Learning Classifier Systems to Control In Vitro Neuronal Networks. In D. Thierens et al. (eds) GECOO-2007: Proceedings of the Genetic and Evolutionary Computation Conference. ACM Press, pp369-376.
[j]
Bull, L. & Uroukov, I. (2008) Towards Neuronal Computing: Simple Creation of Two Logic Functions in 3D Cell Cultures using Multi-Electrode Arrays. Unconventional Computing 4(2): 143-154.
[j]
Bull, L., Budd, A., Stone, C., Uroukov, I., De Lacy Costello, B. & Adamatzky, A. (2008) Towards Unconventional Computing Through Simulated Evolution: Learning Classifier System Control of Non-Linear Media. Artificial Life 14(2): 203-222.
Uroukov, I. & Bull, L. (2008) Mapping The Impact Of Long-Term Electrical Stimulation To Organotypical Hen Embryonic Brain (HEB) Spheroids On Their Spiking Activity. Part I. In Proceedings of the 6th International Meeting on Substrate-Integrated Micro Electrode Arrays. BIOPRO.
Uroukov, I. & Bull, L. (2008) Mapping The Impact Of Long-Term Electrical Stimulation To Organotypical Hen Embryonic Brain (HEB) Spheroids On Their Spiking Activity. Part II. In Proceedings of the 6th International Meeting on Substrate-Integrated Micro Electrode Arrays. BIOPRO.
[j]
Uroukov, I. & Bull, L. (2008) On the Effect of Long-Term Electrical Stimulation on 3-Dimensional Cell Cultures: Hen Embryo Brain Spheroids. Medical Devices: Evidence and Research 1: 1-12.
[j]
Miranda, E.R., Bull, L., Gueguen, F. & Uroukov, I. (2009) Computer Music Meets Unconventional Computing: Towards Sound Synthesis with In Vitro Neuronal Networks. Computer Music Journal 33(1): 9-18.
Tekiner, F., Pettipher, M, Bull, L. & Bagnall, A. (eds)(2007) Mediterranean Journal of Computers and Networks: Special Issue on Data Mining in Supercomputer and Grid Environments. SoftMotor.
Non-Evolutionary: Ensembles and Features
Bagnall, A., Whittley, I., Studley, M., Tekiner, F., Pettipher, M. & Bull, L. (2006) Variance Stabilizing Regression Ensembles for Environmental Models. In
Proceedings of the IEEE International Joint Conference on Neural Networks. IEEE Press, pp5355-5361.
Bagnall, A., Whittley, I., Janacek, G., Kemsley, K., Studley, M. & Bull, L. (2006) A Comparison of DWA/PAA and DFT for Time Series Classification. In
Proceedings of the 2006 International Conference on Data Mining. CSREA Press, pp403-409.
Whittley, I.M., Bagnall, A.J., Bull, L., Pettipher, M., Studley, M. & Tekiner, F. (2006) Attribute Selection Methods for Filtered Attribute Subspace based Bagging with Injected Randomness (FASBIR). In Feature Selection for Data Mining Workshop, Part of the 2006 SIAM Conference on Data Mining.
[j]
Bagnall, A., Cawley, G., Whittley, I., Bull, L., Studley, M, Tekiner, F. & Pettipher, M. (2007) Super Computer Heterogeneous Classifier Meta-Ensembles. International Journal of Data Warehousing and Mining 3(2): 67-82
[b]
Bagnall, A., Cawley, G., Whittley, I., Bull, L., Studley, M, Tekiner, F. & Pettipher, M. (2008) Super Computer Heterogeneous Classifier Meta-Ensembles. In J. Wang (ed) Data Warehousing and Mining: Concepts, Methodologies, Tools and Applications. IGI Global, pp1320-1333.
Genetic Programming
Smith, M. & Bull, L. (2003) Feature Construction and Selection using Genetic Programming and a Genetic Algorithm. In
C. Ryan, T. Soule, E. Tsang, R. Poli & E. Costa (eds) Genetic Programming: Proceedings of 6th European Conference, EuroGP 2003. Springer, pp229-237.
[b]
Smith, M. & Bull, L. (2004) GAP: Constructing and Selecting Features with Evolutionary Computing. In A. Gosh & L. Jain (eds)
Evolutionary Computation in Data Mining. Springer, pp41-56.
Smith, M. & Bull, L. (2004) Using Genetic Programming for Feature Creation with a Genetic Algorithm Feature Selector.
In X. Yao et al. (eds) Parallel Problem Solving from Nature - PPSN VIII. Springer Verlag, pp1163-1171.
[j]
Smith, M. & Bull, L. (2005) Genetic Programming with a Genetic Algorithm for Feature Construction and Selection.
Genetic Programming and Evolvable Machines 6(3): 265-281.
Smith, M. & Bull, L. (2007) Improving the Human Readability of Features Constructed by Genetic Programming. In D. Thierens et al. (eds) GECOO-2007: Proceedings of the Genetic and Evolutionary Computation Conference. ACM Press, pp1694-1701.
Creation and use through evolutionary design of memristors, with Andy Adamatzky (PI) and Ben De Lacy Costello.
HEAT@UWE: Bridging the gaps in Health, Environment And Technology (HEAT) research (EPSRC: 2009-2012)
Initiative to form new multi-disciplined research themes across UWE, led by Katie Williams (PI).
Discrete Dynamical Systems with Memory: A New Tool for Modelling Complexity (EPSRC: Ramon Alonso-Sanz, Chris Stone, 2007-2009)
Exploring the use of memory in systems such as cellular automata, with Andy Adamatzky.
Mining Olympic Sailing Boat Telemetry Data (EPSRC: Julian Holley, 2007-2008)
Using machine learning to explore Olympic team data, in collaboration with UK Sport.
Machine Learning Mining of Cricket Test Data (English Cricket Board: Consultancy, 2007-2008)
Using machine learning to explore match data.
Mining Athlete Event Data (EPSRC: Ian Whittley, 2007-2008)
Using machine learning to explore Olympic athlete data, in collaboration with UK Sport.
Evolutionary Design of Collison-based Computing Schemes in Two-dimensional Cellular Automata (EPSRC: Emmanuel Sapin, 2006-2007)
Exploring the use of genetic algorithms to design architecture-less computers, with Andy Adamatzky (PI).
AJ-SINIC: Anglo-Japanese Initiative in Non-Linear Media Computing (EPSRC: 2005-2006)
Establishment of a collaborative network in non-classical computation based on principles of information processing in physical and chemical media, with Andy Adamatzky (PI)
and Ben DeLacyCostello.
Non-Linear Media Based Computers (EPSRC: Mingwen Ma, Chris Stone, Rita Toth and Ivan Uroukov, 2004-2008)
Novel Computation project to develop and test a new approach to enable desired computations/behaviour from networks of non-linear media, in collaboration with Sussex and Leeds.
Super-Computer Data Mining (EPSRC: Matthew Studley, 2004-2006)
Creation of a UK machine learning data mining tool, in collaboration with Manchester and UEA.
Cluster on Non-Linear Media Based Computers (EPSRC: 2003-2004)
Novel Computation cluster, in collaboration with Andy Adamatzky (PI)
and Ben DeLacyCostello.
A Learning Classifier System Approach to Neural Constructivism (EPSRC ROPA: Jacob Hurst, 2002-2004)
Use of LCS to control mobile robots where each rule is a neural network and their complexity emerges during learning.
Data Mining (LloydsTSB: Praminda Caleb-Solly, 2001-2003)
Project to use a number of machine learning techniques for
analysis of various types of financial data.
Distributed Adaptive Control for Road Traffic Systems (EPSRC: Andy Tomlinson, 2001-2003)
A project applying LCS to
road traffic signal control in collaboration with the traffic group at UCL.
Evolutionary Robotics (BT Labs & UWE CollR: Jacob Hurst, 1999-2002)
A project using self-adaptive LCS for learning in mobile robot systems.
Vintage (EU ESPRIT: YiJa Cao and Neil Ireson, 1998-2000)
A European project which built a distributed
LCS kernel, with applications in distributed control and scheduling.
