Abstract
In a general Markov decision progress system, only one agent’s learning evolution is considered. However, considering the learning evolution of a single agent in many problems has some limitations, more and more applications involve multi-agent. There are two types of cooperation, game environment among multi-agent. Therefore, this paper introduces a Cooperation Markov Decision Process system with two agents, which is suitable for the learning evolution of cooperative decision between two agents. It is further found that the value function in the system also converges in the end, and the convergence value is independent of the choice of the value of the initial value function. This paper presents an algorithm for finding the optimal strategy pair in the system, whose fundamental task is to find an optimal strategy pair and form an evolutionary system . Finally, an example is given to support the theoretical results.
Highlights
Artificial intelligence technology has become one of the most important technologies, nowadays.AlphaGo, unmanned driving, voice recognition, face recognition and other well-known technologies involve artificial intelligence
This paper presents an algorithm for finding the optimal strategy pair in the Cooperation Markov Decision Process (CMDP) system, whose fundamental task is to find an optimal strategy pair and form an evolutionary system CMDP
This paper only considers the Cooperation Markov Decision Process (CMDP) system of two agents, which is suitable for the evolutionary learning system of cooperative decision between two agents
Summary
Artificial intelligence technology has become one of the most important technologies, nowadays. The important basis of reinforcement learning [5] is Markov Decision Process ( MDP) system [6]. Two-agent games for multi-agent reinforcement learning are similar to perceptrons for neural networks.In this kind of learning model, agents alternately execute behaviors, seek optimal criteria based on social value, seek optimal strategies (πk0 , πk1 ) , and jointly complete the target task. This paper introduces a cooperation Markov decision process system in the form of definition, two trade agent (Alice and Bob) on the basis of its strategy to perform an action. The convergence property of the value function of the MDP system with the participation of a single agent is given, the convergence phenomenon of the value function in the cooperation Markov decision process system proposed in this paper is further explored, and the correctness of the property is proved from both the experimental and theoretical perspectives
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