Adaptive action selection for cooperative agent teams
Proceedings of the second international conference on From animals to animats 2 : simulation of adaptive behavior: simulation of adaptive behavior
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
An introduction to natural computation
An introduction to natural computation
Machine Learning
IEEE Transactions on Neural Networks
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This paper presents the hexagon-based Q-leaning to find a hidden target object with multiple robots. We set up an experimental environment with three small mobile robots, obstacles, and a target object. The robots were out to search for a target object while navigating in a hallway where some obstacles were placed. In this experiment, we used two control algorithms: an area-based action making (ABAM) process to determine the next action of the robots and hexagon-based Q-learning to enhance the area-based action making process.