Title : 
Cooperative behavior acquisition in multi-mobile robots environment by reinforcement learning based on state vector estimation
         
        
            Author : 
Uchibe, Eiji ; Asada, Minoru ; Hosoda, Koh
         
        
            Author_Institution : 
Graduate Sch. of Eng., Osaka Univ., Japan
         
        
        
        
        
            Abstract : 
This paper proposes a method that acquires robots´ behaviors based on the estimation of the state vectors. In order to acquire the cooperative behaviors in multi-robot environments, each learning robot estimates the local predictive model between the learner and the other objects separately. Based on the local predictive models, the robots learn the desired behaviors using reinforcement learning. The proposed method is applied to a soccer playing situation, where a rolling ball and other moving robots are well modeled and the learner´s behaviors are successfully acquired by the method. Computer simulations and real experiments are shown and a discussion is given
         
        
            Keywords : 
cooperative systems; learning (artificial intelligence); mobile robots; predictive control; software agents; state estimation; behaviour based control; cooperative systems; multiple agents; multiple mobile robots; predictive models; reinforcement learning; state vector estimation; Adaptive systems; Artificial intelligence; High performance computing; Learning; Mobile robots; Neurons; Predictive models; Robot kinematics; Robot sensing systems; State estimation;
         
        
        
        
            Conference_Titel : 
Robotics and Automation, 1998. Proceedings. 1998 IEEE International Conference on
         
        
            Conference_Location : 
Leuven
         
        
        
            Print_ISBN : 
0-7803-4300-X
         
        
        
            DOI : 
10.1109/ROBOT.1998.677351