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» Solving Complex Problems Efficiently with Adaptive Automata
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SASO
2008
IEEE
15 years 9 months ago
Leveraging Organizational Guidance Policies with Learning to Self-Tune Multiagent Systems
As organization-based multiagent systems are applied to more complex problems, configuring and tuning the systems can become nearly as complex as the original problem a system wa...
Scott J. Harmon, Scott A. DeLoach, Robby, Doina Ca...
161
Voted
PAMI
2012
13 years 5 months ago
Task-Driven Dictionary Learning
—Modeling data with linear combinations of a few elements from a learned dictionary has been the focus of much recent research in machine learning, neuroscience, and signal proce...
Julien Mairal, Francis Bach, Jean Ponce
UAI
2008
15 years 4 months ago
CORL: A Continuous-state Offset-dynamics Reinforcement Learner
Continuous state spaces and stochastic, switching dynamics characterize a number of rich, realworld domains, such as robot navigation across varying terrain. We describe a reinfor...
Emma Brunskill, Bethany R. Leffler, Lihong Li, Mic...
RSCTC
2000
Springer
197views Fuzzy Logic» more  RSCTC 2000»
15 years 7 months ago
Rough Set Approach to CBR
We discuss how Case Based Reasoning (CBR) (see e.g. [1], [4]) philosophy of adaptation of some known situations to new similar ones can be realized in rough set framework [5] for c...
Jan Wierzbicki
128
Voted
IJCAI
1997
15 years 4 months ago
Development of Iterative Real-time Scheduler to Planner Feedback
Planning for real-time applications involves decisions not only about what actions to take in what states to progress toward achieving goals (the traditional decision problem face...
Charles B. McVey, Ella M. Atkins, Edmund H. Durfee...