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108
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AIPS
1996
15 years 3 months ago
1996
Learning from experimentation allows a system to acquire planning domain knowledge by correcting its knowledge when an action execution fails. Experiments are designed and planned...
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AGENTS
1999
Springer
15 years 6 months ago
1999
Springer
We describe the interface between a real-time resource allocation system with an AI planner in order to create fault-tolerant plans that are guaranteed to execute in hard real-tim...
KR
2010
Springer
15 years 6 months ago
2010
Springer
A plan with rich control structures like branches and loops can usually serve as a general solution that solves multiple planning instances in a domain. However, the correctness o...
ECP
1997
Springer
15 years 6 months ago
1997
Springer
It is traditional wisdom that one should start from the goals when generating a plan in order to focus the plan generation process on potentially relevant actions. The graphplan sy...
AAAI
2008
15 years 4 months ago
2008
This paper addresses the problem of plan recognition for multi-agent teams. Complex multi-agent tasks typically require dynamic teams where the team membership changes over time. ...