LIVE: an architecture for learning from the environment
ACM SIGART Bulletin
RoboCup: The Robot World Cup Initiative
AGENTS '97 Proceedings of the first international conference on Autonomous agents
Basic agents for visual/motor coordination of a mobile robot
AGENTS '97 Proceedings of the first international conference on Autonomous agents
A Probabilistic Approach to Concurrent Mapping and Localization for Mobile Robots
Machine Learning - Special issue on learning in autonomous robots
Autonomous Learning from the Environment
Autonomous Learning from the Environment
Preface for Special Section on Integrated Cognitive Architectures
ACM SIGART Bulletin
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The annual robot soccer competition (RoboCup) provides an excellent opportunity for research in distributed robotic systems. A robotic soccer team demands integrated robots that are autonomous, efficient, cooperative, and intelligent. In this paper, we introduce the concept of Purposeful Behavior, to tackle the problem of achieving reactive and coordinated behavior in a team of autonomous robots. We are building a new control framework for autonomous robots to reason about goals and actions, react to unexpected situations, learn from humans and experience, and collaborate with teammates. Building such robots may require techniques that are different from those employed in separate research disciplines. We describe our experience in building these soccer robots and highlights problems and solutions that are unique to such multi-agent robotic systems in general. These problems include a framework for multi-agent programming, agent modeling and architecture, evaluation of multi-agent systems, and decentralized skill composition.