Sequence-Learning Algorithm Based on Backward Chaining
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Application of stochastic learning automata to intelligent vehicle control
ICCOMP'07 Proceedings of the 11th WSEAS International Conference on Computers
An ASML model for an intelligent vehicle control system
ICCOMP'07 Proceedings of the 11th WSEAS International Conference on Computers
A new evolutionary reinforcement scheme for stochastic learning automata
ICCOMP'08 Proceedings of the 12th WSEAS international conference on Computers
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MAMECTIS'08 Proceedings of the 10th WSEAS international conference on Mathematical methods, computational techniques and intelligent systems
Partial Local FriendQ Multiagent Learning: Application to Team Automobile Coordination Problem
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Modeling a student's behavior in a tutorial-like system using learning automata
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A new nonlinear reinforcement scheme for stochastic learning automata
ACMOS'10 Proceedings of the 12th WSEAS international conference on Automatic control, modelling & simulation
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A nonlinear reinforcement scheme for stochastic learning automata
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Partial local friendq multiagent learning: application to team automobile coordination problem
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Learning automata as a basis for multi agent reinforcement learning
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Wireless Personal Communications: An International Journal
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This paper suggests an intelligent controller for an automated vehicle planning its own trajectory based on sensor and communication data. The intelligent controller is designed using the learning stochastic automata theory. Using the data received from on-board sensors, two automata (one for lateral actions, one for longitudinal actions) can learn the best possible action to avoid collisions. The system has the advantage of being able to work in unmodeled stochastic environments, unlike adaptive control methods or expert systems. Simulations for simultaneous lateral and longitudinal control of a vehicle provide encouraging results