Induction: processes of inference, learning, and discovery
Induction: processes of inference, learning, and discovery
Distributed problem solving techniques: A survey
IEEE Transactions on Systems, Man and Cybernetics
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Genetic programming (videotape): the movie
Genetic programming (videotape): the movie
Proceedings of the 6th International Conference on Genetic Algorithms
On ZCS in Multi-agent Environments
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
The Fuzzy Classifier System: Motivations and first Results
PPSN I Proceedings of the 1st Workshop on Parallel Problem Solving from Nature
A Fuzzy Classifier System Using the Pittsburgh Approach
PPSN III Proceedings of the International Conference on Evolutionary Computation. The Third Conference on Parallel Problem Solving from Nature: Parallel Problem Solving from Nature
A learning system based on genetic adaptive algorithms
A learning system based on genetic adaptive algorithms
Zcs: A zeroth level classifier system
Evolutionary Computation
Evolving control laws for a network of traffic signals
GECCO '96 Proceedings of the 1st annual conference on Genetic and evolutionary computation
A Learning Classifier Systems Bibliography
Learning Classifier Systems, From Foundations to Applications
A Roadmap to the Last Decade of Learning Classifier System Research
Learning Classifier Systems, From Foundations to Applications
A Bigger Learning Classifier Systems Bibliography
IWLCS '00 Revised Papers from the Third International Workshop on Advances in Learning Classifier Systems
A Collaborative Reinforcement Learning Approach to Urban Traffic Control Optimization
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 02
Coordination of urban intersection agents based on multi-interaction history learning method
ICSI'10 Proceedings of the First international conference on Advances in Swarm Intelligence - Volume Part II
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Traffic control in large cities is a difficult and non-trivial optimization problem. Most of the automated urban traffic control systems are based on deterministic algorithms and have a multi-level architecture; to achieve global optimality, hierarchical control algorithms are generally employed. However, these algorithms are often slow to react to varying conditions, and it has been recognized that incorporating computational intelligence into the lower levels can remove some burdens of algorithm calculation and decision making from higher levels. An alternative approach is to use a fully distributed architecture in which there is effectively only one (low) level of control. Such systems are aimed at increasing the response time of the controller and, again, these often incorporate computational intelligence techniques. This paper presents preliminary work into designing an intelligent local controller primarily for distributed traffic control systems. The idea is to use a classifier system with a fuzzy rule representation to determine useful junction control rules within the dynamic environment.