36 search results - page 5 / 8 » Using Linear Programming for Bayesian Exploration in Markov ... |
ANOR
2010
13 years 6 months ago
2010
Abstract In the controlled ovary hyperstimulation (COH) cycle of the in vitro fertilization-embryo transfer (IVFET) therapy, the clinicians observe the patients' responses to ...
AAAI
2006
13 years 8 months ago
2006
DTGolog, a decision-theoretic agent programming language based on the situation calculus, was proposed to ease some of the computational difficulties associated with Markov Decisi...
AAAI
2006
13 years 8 months ago
2006
Markov decision processes (MDPs) with discrete and continuous state and action components can be solved efficiently by hybrid approximate linear programming (HALP). The main idea ...
PKDD
2010
Springer
13 years 5 months ago
2010
Springer
Abstract. Bayesian reinforcement learning (RL) is aimed at making more efficient use of data samples, but typically uses significantly more computation. For discrete Markov Decis...
AAAI
2000
13 years 8 months ago
2000
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 ...