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AIIDE
2006
13 years 10 months ago
The Self Organization of Context for Learning in MultiAgent Games
Reinforcement learning is an effective machine learning paradigm in domains represented by compact and discrete state-action spaces. In high-dimensional and continuous domains, ti...
Christopher D. White, Dave Brogan
ICML
2005
IEEE
14 years 10 months ago
Combining model-based and instance-based learning for first order regression
T ORDER REGRESSION (EXTENDED ABSTRACT) Kurt Driessensa Saso Dzeroskib a Department of Computer Science, University of Waikato, Hamilton, New Zealand (kurtd@waikato.ac.nz) b Departm...
Kurt Driessens, Saso Dzeroski
IROS
2007
IEEE
179views Robotics» more  IROS 2007»
14 years 3 months ago
Incremental learning for place recognition in dynamic environments
Abstract— Vision-based place recognition is a desirable feature for an autonomous mobile system. In order to work in realistic scenarios, visual recognition algorithms should be ...
Jie Luo, Andrzej Pronobis, Barbara Caputo, Patric ...
CDC
2009
IEEE
107views Control Systems» more  CDC 2009»
14 years 1 months ago
Learning approaches to the Witsenhausen counterexample from a view of potential games
— Since Witsenhausen put forward his remarkable counterexample in 1968, there have been many attempts to develop efficient methods for solving this non-convex functional optimiz...
Na Li, Jason R. Marden, Jeff S. Shamma
ESANN
2004
13 years 10 months ago
Learning by geometrical shape changes of dendritic spines
The role of dendritic spines in neuronal information processing is still not completely clear. However, it is known that spines can change shape rapidly during development and duri...
Andreas Herzog, Vadym Spravedlyvyy, Karsten Kube, ...