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» Decision Making with Partially Consonant Belief Functions
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AAAI
2006
14 years 11 months ago
Incremental Least Squares Policy Iteration for POMDPs
We present a new algorithm, called incremental least squares policy iteration (ILSPI), for finding the infinite-horizon stationary policy for partially observable Markov decision ...
Hui Li, Xuejun Liao, Lawrence Carin
CIMCA
2008
IEEE
15 years 4 months ago
Tree Exploration for Bayesian RL Exploration
Research in reinforcement learning has produced algorithms for optimal decision making under uncertainty that fall within two main types. The first employs a Bayesian framework, ...
Christos Dimitrakakis
SIGMOD
2005
ACM
123views Database» more  SIGMOD 2005»
15 years 3 months ago
To Do or Not To Do: The Dilemma of Disclosing Anonymized Data
Decision makers of companies often face the dilemma of whether to release data for knowledge discovery, vis a vis the risk of disclosing proprietary or sensitive information. Whil...
Laks V. S. Lakshmanan, Raymond T. Ng, Ganesh Rames...
ICTAI
2005
IEEE
15 years 3 months ago
Planning with POMDPs Using a Compact, Logic-Based Representation
Partially Observable Markov Decision Processes (POMDPs) provide a general framework for AI planning, but they lack the structure for representing real world planning problems in a...
Chenggang Wang, James G. Schmolze
UAI
2001
14 years 11 months ago
Similarity Measures on Preference Structures, Part II: Utility Functions
In previous work [8] we presented a casebased approach to eliciting and reasoning with preferences. A key issue in this approach is the definition of similarity between user prefe...
Vu A. Ha, Peter Haddawy, John Miyamoto