A study on robot task planning problems in multiagent environments
Takashi Kawakami, Yukinori Kakazu · 2002
Attempts to realize an autonomous solving mechanism for a task planning problem by a machine learning system. As a robot task planning problem, the block stacking problem is treated. It is well known as one of the most difficult problems. In particular the difficulties of this problem increase in a multiagent environment where multiple robots exist in a problem domain and they cooperate or negotiate to achieve given tasks effectively. To realize an autonomous planning mechanism, a classifier system is applied to this problem. In this approach, a classifier corresponds to a production rule that instructs the next operation when its conditional part is fully matched for a current state. Each robot has an individual classifier system as the robot task planner.