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IAT
2005
IEEE
13 years 11 months ago
Decomposing Large-Scale POMDP Via Belief State Analysis
Partially observable Markov decision process (POMDP) is commonly used to model a stochastic environment with unobservable states for supporting optimal decision making. Computing ...
Xin Li, William K. Cheung, Jiming Liu
IJCAI
2007
13 years 7 months ago
Inside-Outside Probability Computation for Belief Propagation
In this paper we prove that the well-known correspondence between the forward-backward algorithm for hidden Markov models (HMMs) and belief propagation (BP) applied to HMMs can be...
Taisuke Sato
AAAI
2006
13 years 7 months ago
A Computational Model of Logic-Based Negotiation
This paper presents a computational model of negotiation based on Nebel's syntax-based belief revision. The model guarantees a unique bargaining solution for each bargaining ...
Dongmo Zhang, Yan Zhang
ATAL
2005
Springer
13 years 11 months ago
A computationally grounded logic of knowledge, belief and certainty
This paper presents a logic of knowledge, belief and certainty, which allows us to explicitly express the knowledge, belief and certainty of an agent. A computationally grounded m...
Kaile Su, Abdul Sattar, Guido Governatori, Qinglia...
CSE
2009
IEEE
13 years 9 months ago
Satisficing the Masses: Applying Game Theory to Large-Scale, Democratic Decision Problems
ACT We present ongoing research on large-scale decision models in which there are many invested individuals. We apply our unique Bayesian belief aggregation approach to decision pr...
Kshanti A. Greene, Joe Michael Kniss, George F. Lu...