Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Evolutionary learning of communicating agents
Information Sciences—Informatics and Computer Science: An International Journal
Minimax real-time heuristic search
Artificial Intelligence - Special issue on heuristic search in artificial intelligence
Introduction to AI Robotics
An Behavior-based Robotics
Coevolving and cooperating path planner for multiple unmanned air vehicles
Engineering Applications of Artificial Intelligence
IEEE Transactions on Evolutionary Computation
Model-based learning for mobile robot navigation from the dynamicalsystems perspective
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Spatial learning for navigation in dynamic environments
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Population variation in genetic programming
Information Sciences: an International Journal
Fidelity-guaranteed robustness enhancement of blind-detection watermarking schemes
Information Sciences: an International Journal
Dynamic population variation in genetic programming
Information Sciences: an International Journal
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Strategy planning is crucial to control a group to achieve a number of tasks in a closed area full of obstacles. In this study, genetic programming has been used to evolve rule-based hierarchical structures to move the particles in a grid region to accomplish navigation tasks. Communications operations such as receiving and sending commands between particles are also provided to develop improved strategies. In order to produce more capable strategies, a task decomposition procedure is proposed. In addition, a conflict module is constructed to handle the challenging situations and conflicts such as blockage of a particle's pathway to destination by other particles.