Systems, Man, and Cybernetics

 

Home

• [P624] An Experimental Adaptive Fuzzy Controller for Differential Games
  Author(s): Sidney Givigi, Howard M. Schwartz, Xiaosong Lu
  
  

  Abstract
  In this paper a reinforcement fuzzy learning scheme for robots playing a differential game is derived. A differential game may be considered a Markov decision process in continuous time, with continuous states and actions. The robots receive reinforcements from the environment after they take an action; and this reinforcement is then used to adapt a fuzzy controller that stores the experience accumulated by the robot. Every calculation is done in a physical system based on microcontrollers to control the movement of the robots and sensors to measure their position and angle in a 2D-plane. Filters are also implemented to approximate the derivatives of the states. Experiments of a pursuer-evader game are provided in order to show the feasibility of the technique. It should be noted, though, that the technique may also be used in a multi-game environment.

  
   

Full Text (PDF)