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» A Meta-CSP Model for Optimal Planning
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IAT
2010
IEEE
13 years 7 months ago
Selecting Operator Queries Using Expected Myopic Gain
When its human operator cannot continuously supervise (much less teleoperate) an agent, the agent should be able to recognize its limitations and ask for help when it risks making...
Robert Cohn, Michael Maxim, Edmund H. Durfee, Sati...
CONSTRAINTS
2010
126views more  CONSTRAINTS 2010»
13 years 6 months ago
Solving satisfiability problems with preferences
Abstract. Propositional satisfiability (SAT) is a success story in Computer Science and Artificial Intelligence: SAT solvers are currently used to solve problems in many different ...
Emanuele Di Rosa, Enrico Giunchiglia, Marco Marate...
AAAI
2000
13 years 10 months ago
Decision Making under Uncertainty: Operations Research Meets AI (Again)
Models for sequential decision making under uncertainty (e.g., Markov decision processes,or MDPs) have beenstudied in operations research for decades. The recent incorporation of ...
Craig Boutilier
AAAI
2006
13 years 10 months ago
LOCATE Intelligent Systems Demonstration: Adapting Help to the Cognitive Styles of Users
LOCATE is workspace layout design software that also serves as a testbed for developing and refining principles of adaptive aiding. This demonstration illustrates LOCATE's ab...
Jack L. Edwards, Greg Scott
AAAI
1997
13 years 10 months ago
Model Minimization in Markov Decision Processes
Many stochastic planning problems can be represented using Markov Decision Processes (MDPs). A difficulty with using these MDP representations is that the common algorithms for so...
Thomas Dean, Robert Givan