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» Learning probabilistic decision graphs
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RECOMB
2005
Springer
16 years 3 months ago
The Factor Graph Network Model for Biological Systems
Abstract. We introduce an extended computational framework for studying biological systems. Our approach combines formalization of existing qualitative models that are in wide but ...
Irit Gat-Viks, Amos Tanay, Daniela Raijman, Ron Sh...
151
Voted
AAAI
2000
15 years 5 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
152
Voted
NIPS
2008
15 years 5 months ago
Goal-directed decision making in prefrontal cortex: a computational framework
Research in animal learning and behavioral neuroscience has distinguished between two forms of action control: a habit-based form, which relies on stored action values, and a goal...
Matthew Botvinick, James An
126
Voted
ALT
2006
Springer
16 years 17 days ago
Asymptotic Learnability of Reinforcement Problems with Arbitrary Dependence
We address the problem of reinforcement learning in which observations may exhibit an arbitrary form of stochastic dependence on past observations and actions. The task for an age...
Daniil Ryabko, Marcus Hutter
112
Voted
UM
2005
Springer
15 years 9 months ago
Bayesphone: Precomputation of Context-Sensitive Policies for Inquiry and Action in Mobile Devices
Inference and decision making with probabilistic user models may be infeasible on portable devices such as cell phones. We highlight the opportunity for storing and using precomput...
Eric Horvitz, Paul Koch, Raman Sarin, Johnson Apac...