Hybrid System of Reinforcement Learning and Flocking Control in Multi-robot Domain
نویسندگان
چکیده
In multi-robot domain, one of the important problems is to achieve cooperation among robots. In this paper we propose a hybrid system that integrates reinforcement learning and flocking control in order to create adaptive and intelligent multi-robot systems. We study two problems of multi-robot concurrent learning of cooperative behaviors: (1) how to generate efficient combination of high level behaviors (discrete states and actions) and low level behavior (continuous states and actions) for multi-robot cooperation; (2) how to coordinate concurrent learning process in a distributed fashion. To evaluate our theoretic framework we apply it to solve the problem of how a multi-robot network learns to avoid predator while maintaining network topology and connectivity. The experiments and simulations are performed to demonstrate the effectiveness of the proposed hybrid system.
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تاریخ انتشار 2016