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» Sampling Methods for Action Selection in Influence Diagrams
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AAAI
2000
13 years 6 months ago
Sampling Methods for Action Selection in Influence Diagrams
Sampling has become an important strategy for inference in belief networks. It can also be applied to the problem of selecting actions in influence diagrams. In this paper, we pre...
Luis E. Ortiz, Leslie Pack Kaelbling
UAI
2000
13 years 6 months ago
Adaptive Importance Sampling for Estimation in Structured Domains
Sampling is an important tool for estimating large, complex sums and integrals over highdimensional spaces. For instance, importance sampling has been used as an alternative to ex...
Luis E. Ortiz, Leslie Pack Kaelbling
UAI
2008
13 years 6 months ago
Strategy Selection in Influence Diagrams using Imprecise Probabilities
This paper describes a new algorithm to solve the decision making problem in Influence Diagrams based on algorithms for credal networks. Decision nodes are associated to imprecise...
Cassio Polpo de Campos, Qiang Ji
IROS
2007
IEEE
123views Robotics» more  IROS 2007»
13 years 11 months ago
Reinforcement learning in multi-dimensional state-action space using random rectangular coarse coding and Gibbs sampling
: This paper presents a coarse coding technique and an action selection scheme for reinforcement learning (RL) in multi-dimensional and continuous state-action spaces following con...
Kimura Kimura
AIMSA
1998
Springer
13 years 9 months ago
Knowledge Granularity and Action Selection
Abstract. In this paper we introduce the concept of knowledge granularity and study its influence on an agent's action selection process. Action selection is critical to an ag...
Yiming Ye, John K. Tsotsos