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» AI planning: solutions for real world problems
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AI
2008
Springer
13 years 7 months ago
Sequential Monte Carlo in reachability heuristics for probabilistic planning
The current best conformant probabilistic planners encode the problem as a bounded length CSP or SAT problem. While these approaches can find optimal solutions for given plan leng...
Daniel Bryce, Subbarao Kambhampati, David E. Smith
AAAI
2004
13 years 9 months ago
SOFIA's Choice: An AI Approach to Scheduling Airborne Astronomy Observations
We describe an innovative solution to the problem of scheduling astronomy observations for the Stratospheric Observatory for Infrared Astronomy, an airborne observatory. The probl...
Jeremy Frank, Michael A. K. Gross, Elif Kürkl...
AAAI
2000
13 years 8 months ago
Towards Feasible Approach to Plan Checking under Probabilistic Uncertainty: Interval Methods
The main problem of planning is to find a sequence of actions that an agent must perform to achieve a given objective. An important part of planning is checking whether a given pl...
Raul Trejo, Vladik Kreinovich, Chitta Baral
AAAI
2006
13 years 9 months ago
Unifying Logical and Statistical AI
Intelligent agents must be able to handle the complexity and uncertainty of the real world. Logical AI has focused mainly on the former, and statistical AI on the latter. Markov l...
Pedro Domingos, Stanley Kok, Hoifung Poon, Matthew...
COR
2007
157views more  COR 2007»
13 years 7 months ago
A decision support system for the single-depot vehicle rescheduling problem
Disruptions in trips can prevent vehicles from executing their schedules as planned. Mechanical failures, accidents, and traffic congestion often hinder a vehicle schedule. When a...
Jing-Quan Li, Denis Borenstein, Pitu B. Mirchandan...