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WAPCV
2007
Springer
15 years 10 months ago
Learning to Attend - From Bottom-Up to Top-Down
The control of overt visual attention relies on an interplay of bottom-up and top-down mechanisms. Purely bottom-up models may provide a reasonable account of the looking behaviors...
Hector Jasso, Jochen Triesch
CSE
2008
IEEE
15 years 10 months ago
Adaptation to Dynamic Resource Availability in Ad Hoc Grids through a Learning Mechanism
Ad-hoc Grids are highly heterogeneous and dynamic networks, one of the main challenges of resource allocation in such environments is to find mechanisms which do not rely on the ...
Behnaz Pourebrahimi, Koen Bertels
AGENTS
1999
Springer
15 years 8 months ago
General Principles of Learning-Based Multi-Agent Systems
We consider the problem of how to design large decentralized multiagent systems (MAS’s) in an automated fashion, with little or no hand-tuning. Our approach has each agent run a...
David Wolpert, Kevin R. Wheeler, Kagan Tumer
ECAI
2006
Springer
15 years 7 months ago
Strategic Foresighted Learning in Competitive Multi-Agent Games
We describe a generalized Q-learning type algorithm for reinforcement learning in competitive multi-agent games. We make the observation that in a competitive setting with adaptive...
Pieter Jan't Hoen, Sander M. Bohte, Han La Poutr&e...
EPIA
1995
Springer
15 years 7 months ago
Using Stochastic Grammars to Learn Robotic Tasks
Abstract. The paper introduces a reinforcement learning-based methodology for performance improvement of Intelligent Controllers. The translation interfaces of a 3-level Hierarchic...
Pedro U. Lima, George N. Saridis