Domain-independent planning: representation and plan generation
Artificial Intelligence
Brains, Behavior and Robotics
A Robust Layered Control System For a Mobile Robot
A Robust Layered Control System For a Mobile Robot
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Linking perception and action through motivation and affect
Journal of Experimental & Theoretical Artificial Intelligence
Robot task planning using semantic maps
Robotics and Autonomous Systems
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An architecture for adaptive intelligent systems
Artificial Intelligence
Robotics and Autonomous Systems
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AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
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Autonomous Agents and Multi-Agent Systems
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UAI'94 Proceedings of the Tenth international conference on Uncertainty in artificial intelligence
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SOFSEM'06 Proceedings of the 32nd conference on Current Trends in Theory and Practice of Computer Science
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PRIMA'06 Proceedings of the 9th Pacific Rim international conference on Agent Computing and Multi-Agent Systems
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A hierarchical goal-based formalism and algorithm for single-agent planning
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In this paper, the reasoning and planning capabilities of an autonomous mobile robot are described. The reasoning system that controls the robot is designed to exhibit the kind of behavior expected of a rational agent, and is endowed with the psychological attitudes of belief, desire, and intention. Because these attitudes are explicitly represented, they can be manipulated and reasoned about, resulting in complex goal-directed and reflective behaviors. Unlike most planning systems, the plans or intentions formed by the robot need only be partly elaborated before it decides to act. This allows the robot to avoid overly strong expectations about the environment, overly constrained plans of action, and other forms of overcommitment common to previous planners. In addition, the robot is continuously reactive and has the ability to change its goals and intentions as situations warrant. The system has been tested with SRI's autonomous robot (Flakey) in a space station scenario involving navigation and the performance of emergency tasks.