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» Decision Making with Partially Consonant Belief Functions
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AAAI
2006
15 years 8 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
16 years 1 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»
16 years 3 days 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
16 years 4 days 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
15 years 8 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