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The purpose of this paper is to present a novel multi-agent cooperating learning method for the learning agents to share episodes beneficial to the exploitation of the accumulated knowledge and to utilize the learned reinforcement values efficiently. Further, taking the visited times into account, this paper proposes the multi-agent learning method that the learning agents share better policies beneficial...
Reinforcement learning (RL) is an efficient learning method for Markov decision processes (MDPs); ant colony system (ACS) is an efficient method for solving combinatorial optimization problems. Based on the update policy of reinforcement values in RL and the cooperating method of the indirect media communication in ACS, this paper proposes the Q-ACS multi-agent cooperating learning method for the...
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