Zobrazeno 1 - 10
of 942
pro vyhledávání: '"Kambhampati, S"'
Publikováno v:
European Journal of Cardiovascular Medicine. 2023, Vol. 13 Issue 1, p428-434. 7p.
Publikováno v:
Journal Of Artificial Intelligence Research, Volume 24, pages 919-931, 2005
The Optiplan planning system is the first integer programming-based planner that successfully participated in the international planning competition. This engineering note describes the architecture of Optiplan and provides the integer programming fo
Externí odkaz:
http://arxiv.org/abs/1109.2155
Autor:
Kambhampati, S., Sanchez, R.
Publikováno v:
Journal Of Artificial Intelligence Research, Volume 19, pages 631-657, 2003
Despite their near dominance, heuristic state search planners still lag behind disjunctive planners in the generation of parallel plans in classical planning. The reason is that directly searching for parallel solutions in state space planners would
Externí odkaz:
http://arxiv.org/abs/1106.5262
Autor:
Do, M., Kambhampati, S.
Publikováno v:
Journal Of Artificial Intelligence Research, Volume 20, pages 155-194, 2003
SAPA is a domain-independent heuristic forward chaining planner that can handle durative actions, metric resource constraints, and deadline goals. It is designed to be capable of handling the multi-objective nature of metric temporal planning. Our te
Externí odkaz:
http://arxiv.org/abs/1106.5260
Autor:
Kambhampati, S.
Publikováno v:
Journal Of Artificial Intelligence Research, Volume 12, pages 1-34, 2000
This paper reviews the connections between Graphplan's planning-graph and the dynamic constraint satisfaction problem and motivates the need for adapting CSP search techniques to the Graphplan algorithm. It then describes how explanation based learni
Externí odkaz:
http://arxiv.org/abs/1106.0230
Publikováno v:
Journal Of Artificial Intelligence Research, Volume 26, pages 35-99, 2006
Some recent works in conditional planning have proposed reachability heuristics to improve planner scalability, but many lack a formal description of the properties of their distance estimates. To place previous work in context and extend work on heu
Externí odkaz:
http://arxiv.org/abs/1103.1711
Autor:
Srivastava, B., Kambhampati, S.
Publikováno v:
Journal of Artificial Intelligence Research, Vol 8, (1998), 93-128
Existing plan synthesis approaches in artificial intelligence fall into two categories -- domain independent and domain dependent. The domain independent approaches are applicable across a variety of domains, but may not be very efficient in any one
Externí odkaz:
http://arxiv.org/abs/cs/9803101
Autor:
Ihrig, L. H., Kambhampati, S.
Publikováno v:
Journal of Artificial Intelligence Research, Vol 7, (1997), 161-198
Case-Based Planning (CBP) provides a way of scaling up domain-independent planning to solve large problems in complex domains. It replaces the detailed and lengthy search for a solution with the retrieval and adaptation of previous planning experienc
Externí odkaz:
http://arxiv.org/abs/cs/9711102
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