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» Learning Behavior Models for Hybrid Timed Systems
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146
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ATAL
2011
Springer
14 years 3 months ago
Game theory-based opponent modeling in large imperfect-information games
We develop an algorithm for opponent modeling in large extensive-form games of imperfect information. It works by observing the opponent’s action frequencies and building an opp...
Sam Ganzfried, Tuomas Sandholm
191
Voted
AAIP
2009
15 years 4 months ago
Incremental Learning in Inductive Programming
Inductive programming systems characteristically exhibit an exponential explosion in search time as one increases the size of the programs to be generated. As a way of overcoming ...
Robert Henderson
ICMAS
1998
15 years 4 months ago
The Moving Target Function Problem in Multi-Agent Learning
We describe a framework that can be used to model and predict the behavior of MASs with learning agents. It uses a difference equation for calculating the progression of an agent&...
José M. Vidal, Edmund H. Durfee
147
Voted
IUI
2000
ACM
15 years 7 months ago
Learning to recommend from positive evidence
In recent years, many systems and approaches for recommending information, products or other objects have been developed. In these systems, often machine learning methods that nee...
Ingo Schwab, Wolfgang Pohl, Ivan Koychev
152
Voted
RTAS
2006
IEEE
15 years 9 months ago
Bounding Preemption Delay within Data Cache Reference Patterns for Real-Time Tasks
Caches have become invaluable for higher-end architectures to hide, in part, the increasing gap between processor speed and memory access times. While the effect of caches on timi...
Harini Ramaprasad, Frank Mueller