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EUROCAST
2007
Springer
182views Hardware» more  EUROCAST 2007»
14 years 1 months ago
A k-NN Based Perception Scheme for Reinforcement Learning
Abstract a paradigm of modern Machine Learning (ML) which uses rewards and punishments to guide the learning process. One of the central ideas of RL is learning by “direct-online...
José Antonio Martin H., Javier de Lope Asia...
AAAI
2007
13 years 9 months ago
RETALIATE: Learning Winning Policies in First-Person Shooter Games
In this paper we present RETALIATE, an online reinforcement learning algorithm for developing winning policies in team firstperson shooter games. RETALIATE has three crucial chara...
Megan Smith, Stephen Lee-Urban, Hector Muño...
AAAI
2006
13 years 8 months ago
Modeling Human Decision Making in Cliff-Edge Environments
In this paper we propose a model for human learning and decision making in environments of repeated Cliff-Edge (CE) interactions. In CE environments, which include common daily in...
Ron Katz, Sarit Kraus
RAS
2006
138views more  RAS 2006»
13 years 7 months ago
From pixels to multi-robot decision-making: A study in uncertainty
Mobile robots must cope with uncertainty from many sources along the path from interpreting raw sensor inputs to behavior selection to execution of the resulting primitive actions...
Peter Stone, Mohan Sridharan, Daniel Stronger, Gre...
GECCO
2008
Springer
179views Optimization» more  GECCO 2008»
13 years 8 months ago
Emergent architecture in self organized swarm systems for military applications
Many sectors of the military are interested in Self-Organized (SO) systems because of their flexibility, versatility and economics. The military is researching and employing auto...
Dustin J. Nowak, Gary B. Lamont, Gilbert L. Peters...