Intelligence without representation
Artificial Intelligence
Designing emergent behaviors: from local interactions to collective intelligence
Proceedings of the second international conference on From animals to animats 2 : simulation of adaptive behavior: simulation of adaptive behavior
Neural networks: a systematic introduction
Neural networks: a systematic introduction
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
An Behavior-based Robotics
Evolutionary Robotics: The Biology,Intelligence,and Technology
Evolutionary Robotics: The Biology,Intelligence,and Technology
Evolving Vision-Based Flying Robots
BMCV '02 Proceedings of the Second International Workshop on Biologically Motivated Computer Vision
Learning behavior-selection by emotions and cognition in a multi-goal robot task
The Journal of Machine Learning Research
A review of adaptive population sizing schemes in genetic algorithms
GECCO '05 Proceedings of the 7th annual workshop on Genetic and evolutionary computation
Mobile robot navigation using motor schema and fuzzy context dependent behavior modulation
Applied Soft Computing
An improved genetic algorithm with initial population strategy and self-adaptive member grouping
Computers and Structures
Embedded Robotics: Mobile Robot Design and Applications with Embedded Systems
Embedded Robotics: Mobile Robot Design and Applications with Embedded Systems
Dynamic population variation in genetic programming
Information Sciences: an International Journal
Fitness functions in evolutionary robotics: A survey and analysis
Robotics and Autonomous Systems
Fuzzy discrete-event systems under fuzzy observability and a test algorithm
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Development of complex robotic systems using the behavior-based control architecture iB2C
Robotics and Autonomous Systems
IEEE Transactions on Evolutionary Computation
Engineering Applications of Artificial Intelligence
Learning to coordinate behaviors
AAAI'90 Proceedings of the eighth National conference on Artificial intelligence - Volume 2
Oscillatory synchronization model of attention to moving objects
Neural Networks
Behavior-modulation technique in mobile robotics using fuzzy discrete event system
IEEE Transactions on Robotics
Adaptive action selection without explicit communication formultirobot box-pushing
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Navigation Behavior Selection Using Generalized Stochastic Petri Nets for a Service Robot
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Tracking a maneuvering target using neural fuzzy network
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Combination of online clustering and Q-value based GA for reinforcement fuzzy system design
IEEE Transactions on Fuzzy Systems
Evolving neural networks to play checkers without relying on expert knowledge
IEEE Transactions on Neural Networks
Behavior Coordination of Mobile Robotics Using Supervisory Control of Fuzzy Discrete Event Systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Computers & Mathematics with Applications
Neural network Reinforcement Learning for visual control of robot manipulators
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
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The success of a behavior-based system relies largely on its Action Selection Mechanism (ASM) module, which is basically a behavior coordination method of either arbitration or command fusion type. Deciding on the right coordination method for ASM when executing a given mission in an arbitrary environment can be a huge obstacle. Providing the system with some kind of Artificial Intelligence (AI) to deal with the dynamics of a given task would be highly recommended. In this paper, an evolutionary process has been employed in a behavior-based system to generate a suitable ASM based on a system's mission scenario. A Genetic Algorithm (GA) is used to train the weights of a Multi-layer Perceptron (MLP) feed-forward artificial neural network in identifying a suitable formulation of ASM. Implementation of such systems in a target tracking mission has shown positive results. Depending on the mission scenario, the evolved ASM can dynamically manage the coordination method in order to achieve the overall system objective.