Hossein Aminaiee

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In this paper we study learning in cooperative object pushing systems. The proposed approach is based on the idea of learning individual skills and then mapping the required cooperative behaviors on the learned skills. The control point for each individual robot is chosen so as to simplify the design of the reinforcement signal and reduce the role of(More)
In this paper we discuss a learning approach to distributed object pushing. In the proposed approach, first the required individual skills for single-robot object pushing are learned using a fuzzy reinforcement learning method. Then, the robots learn how to coordinate their actions to push the object to the desired configuration cooperatively in a(More)
In this paper a novel mechanism for acquiring shared symbols in multi-agent cooperative task is introduced. Inspired by human communication, a technique is suggested in which learning the behaviors and learning how to communicate are decomposed. Decomposing the shared symbol acquisition into two separate learning phases not only simplifies the learning(More)
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