Dimensions of communication and social organization in multi-agent robotic systems
Proceedings of the second international conference on From animals to animats 2 : simulation of adaptive behavior: simulation of adaptive behavior
Exhaustive Geographic Search with Mobile Robots Along Space-Filling Curves
CRW '98 Proceedings of the First International Workshop on Collective Robotics
Collective Search by Mobile Robots using Alpha-Beta Coordination
CRW '98 Proceedings of the First International Workshop on Collective Robotics
Interaction and Intelligent Behavior
Interaction and Intelligent Behavior
IEEE Transactions on Neural Networks
Adaptive dual heuristic programming based on delta-bar-delta learning rule
ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part III
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An important application of mobile robots is searching a region to locate the origin of a specific phenomenon. A variety of optimization algo-rithms can be employed to locate the target source, which has the maximum intensity of the distribution of some detected function. We propose a neural network based dual heuristic programming (DHP) algorithm to solve the collective robotic search problem. Experiments were carried out to investigate the effect of noise and the number of robots on the task performance, as well as the expenses. The experimental results were compared with those of stochastic optimization algorithm. It showed that the performance of the dual heuristic programming (DHP) is better than the stochastic optimization method.