Automatic Derivation of Finite-State Machines for Behavior Control

Finite-state controllers represent an effective action selection mechanisms widely used in domains such as video-games and mobile robotics. In contrast to the policies obtained from MDPs and POMDPs, finite-state controllers have two advantages: they are often extremely compact, and they are general, applying to many problems and not just one. A limitation of finite-state controllers, on the other hand, is that they are written by hand. In this paper, we address this limitation, presenting a method for deriving controllers automatically from models. The models represent a class of contingent problems where actions are deterministic and some fluents are observable. The problem of deriving a controller is converted into a conformant problem that is solved using classical planners, taking advantage of a complete translation into classical planning introduced recently. The controllers derived are `general' in the sense that they do not solve the original problem only, but many variati...

• Type: Conference
• Year: 2010
• Where: AAAI
• Authors: Blai Bonet, Héctor Palacios, Hector Geffner
• Keywords: AAAI 2010, Action Selection Mechanisms, Finite-state Controllers, Intelligent Agents, Mobile Robotics