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» Action discovery for reinforcement learning
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ICML
1996
IEEE
14 years 8 months ago
Learning Evaluation Functions for Large Acyclic Domains
Some of the most successful recent applications of reinforcement learning have used neural networks and the TD algorithm to learn evaluation functions. In this paper, we examine t...
Justin A. Boyan, Andrew W. Moore
KDD
2000
ACM
162views Data Mining» more  KDD 2000»
13 years 11 months ago
Data Mining from Functional Brain Images
Recent advances in functional brain imaging enable identication of active areas of a brain performing a certain function. Induction of logical formulas describing relations betwee...
Mitsuru Kakimoto, Chie Morita, Yoshiaki Kikuchi, H...
ATAL
2003
Springer
14 years 26 days ago
Team formation and communication restrictions in collectives
A collective of agents often needs to maximize a “world utility” function which rates the performance of an entire system, while subject to communication restrictions among th...
Adrian K. Agogino, Kagan Tumer
KDD
2003
ACM
148views Data Mining» more  KDD 2003»
14 years 8 months ago
Mining concept-drifting data streams using ensemble classifiers
Recently, mining data streams with concept drifts for actionable insights has become an important and challenging task for a wide range of applications including credit card fraud...
Haixun Wang, Wei Fan, Philip S. Yu, Jiawei Han
NIPS
2008
13 years 9 months ago
Psychiatry: Insights into depression through normative decision-making models
Decision making lies at the very heart of many psychiatric diseases. It is also a central theoretical concern in a wide variety of fields and has undergone detailed, in-depth, ana...
Quentin J. M. Huys, Joshua T. Vogelstein, Peter Da...