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AAAI
2006
15 years 6 months ago
Compact, Convex Upper Bound Iteration for Approximate POMDP Planning
Partially observable Markov decision processes (POMDPs) are an intuitive and general way to model sequential decision making problems under uncertainty. Unfortunately, even approx...
Tao Wang, Pascal Poupart, Michael H. Bowling, Dale...
IJCAI
2001
15 years 6 months ago
Complexity of Probabilistic Planning under Average Rewards
A general and expressive model of sequential decision making under uncertainty is provided by the Markov decision processes (MDPs) framework. Complex applications with very large ...
Jussi Rintanen
116
Voted
AIPS
2000
15 years 6 months ago
Representations of Decision-Theoretic Planning Tasks
Goal-directed Markov Decision Process models (GDMDPs) are good models for many decision-theoretic planning tasks. They have been used in conjunction with two different reward stru...
Sven Koenig, Yaxin Liu
NGC
2006
Springer
15 years 4 months ago
Story Planning as Exploratory Creativity: Techniques for Expanding the Narrative Search Space
The authoring of fictional stories is considered a creative process. The purpose of most story authoring is not to invent a new style or genre of story that will be accepted by the...
Mark O. Riedl, R. Michael Young
TASE
2008
IEEE
15 years 4 months ago
Automated Planning and Optimization of Lumber Production Using Machine Vision and Computed Tomography
An automated system for planning and optimization of lumber production using Machine Vision and Computed Tomography (CT) is proposed. Cross-sectional CT images of hardwood logs are...
Suchendra M. Bhandarkar, Xingzhi Luo, Richard F. D...