A formal theory of plan recognition
A formal theory of plan recognition
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A formal theory of plan recognition and its implementation
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A Bayesian model of plan recognition
Artificial Intelligence
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Artificial Intelligence
Coordination techniques for distributed artificial intelligence
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Coordination of Distributed Problem Solvers
Coordination of Distributed Problem Solvers
Explanation-Based Generalization: A Unifying View
Machine Learning
Step-logic: reasoning situated in time
Step-logic: reasoning situated in time
Fundamenta Informaticae
The impact of adversarial knowledge on adversarial planning in perimeter patrol
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Achieving cooperation in a minimally constrained environment
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 1
Using focal point learning to improve tactic coordination in human-machine interactions
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Using focal point learning to improve human---machine tacit coordination
Autonomous Agents and Multi-Agent Systems
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Focal points refer to prominent solutions of an interaction, solutions to which agents are drawn. This paper considers how automated agents could use focal points for coordination in communication‐impoverished situations. Coordination is a central theme of Distributed Artificial Intelligence. Much work in this field can be seen as a search for mechanisms that allow agents with differing knowledge and goals to coordinate their actions for mutual benefit. Additionally, one of the main assumptions of the field is that communication is expensive relative to computation. Thus, coordination techniques that minimize communication are of particular importance. Our purpose in this paper is to consider how to model the process of finding focal points from domain‐independent criteria, under the assumption that agents cannot communicate with one another. We consider two alternative approaches for finding focal points, one based on decision theory, the second on step‐logic. The first provides for a more natural integration of agent utilities, while the second more successfully models the difficulty of finding solutions. For both cases, we present simulations over randomly generated domains that suggest that focal points can act as an effective heuristic for coordination.