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» Learning Partially Observable Deterministic Action Models
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AAAI
2012
11 years 10 months ago
Competing with Humans at Fantasy Football: Team Formation in Large Partially-Observable Domains
We present the first real-world benchmark for sequentiallyoptimal team formation, working within the framework of a class of online football prediction games known as Fantasy Foo...
Tim Matthews, Sarvapali D. Ramchurn, Georgios Chal...
NLPRS
2001
Springer
13 years 12 months ago
GLR Parser with Conditional Action Model(CAM)
There are two different approaches in the LR parsing. The first one is the deterministic approach that performs the only one action using the control rules learned without any LR ...
Yong-Jae Kwak, Young-Sook Hwang, Hoo-Jung Chung, S...
AI
2007
Springer
13 years 7 months ago
Learning action models from plan examples using weighted MAX-SAT
AI planning requires the definition of action models using a formal action and plan description language, such as the standard Planning Domain Definition Language (PDDL), as inp...
Qiang Yang, Kangheng Wu, Yunfei Jiang
ECML
2007
Springer
14 years 1 months ago
Safe Q-Learning on Complete History Spaces
In this article, we present an idea for solving deterministic partially observable markov decision processes (POMDPs) based on a history space containing sequences of past observat...
Stephan Timmer, Martin Riedmiller