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IJCNN
2008
IEEE
15 years 4 months ago
Learning to select relevant perspective in a dynamic environment
— When an agent observes its environment, there are two important characteristics of the perceived information. One is the relevance of information and the other is redundancy. T...
Zhihui Luo, David A. Bell, Barry McCollum, Qingxia...
SIGDIAL
2010
14 years 7 months ago
Modeling Spoken Decision Making Dialogue and Optimization of its Dialogue Strategy
This paper presents a spoken dialogue framework that helps users in making decisions. Users often do not have a definite goal or criteria for selecting from a list of alternatives...
Teruhisa Misu, Komei Sugiura, Kiyonori Ohtake, Chi...
NIPS
2003
14 years 11 months ago
Policy Search by Dynamic Programming
We consider the policy search approach to reinforcement learning. We show that if a “baseline distribution” is given (indicating roughly how often we expect a good policy to v...
J. Andrew Bagnell, Sham Kakade, Andrew Y. Ng, Jeff...
AIPS
2008
15 years 9 days ago
Learning Heuristic Functions through Approximate Linear Programming
Planning problems are often formulated as heuristic search. The choice of the heuristic function plays a significant role in the performance of planning systems, but a good heuris...
Marek Petrik, Shlomo Zilberstein
IJCAI
2003
14 years 11 months ago
Use of Off-line Dynamic Programming for Efficient Image Interpretation
An interpretation system finds the likely mappings from portions of an image to real-world objects. An interpretation policy specifies when to apply which imaging operator, to whi...
Ramana Isukapalli, Russell Greiner