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ATAL
2005
Springer
15 years 3 months ago
Approximating state estimation in multiagent settings using particle filters
State estimation consists of updating an agent’s belief given executed actions and observed evidence to date. In single agent environments, the state estimation can be formalize...
Prashant Doshi, Piotr J. Gmytrasiewicz
JAIR
2011
187views more  JAIR 2011»
14 years 4 months ago
A Monte-Carlo AIXI Approximation
This paper describes a computationally feasible approximation to the AIXI agent, a universal reinforcement learning agent for arbitrary environments. AIXI is scaled down in two ke...
Joel Veness, Kee Siong Ng, Marcus Hutter, William ...
AAAI
2011
13 years 9 months ago
Incorporating Boosted Regression Trees into Ecological Latent Variable Models
Important ecological phenomena are often observed indirectly. Consequently, probabilistic latent variable models provide an important tool, because they can include explicit model...
Rebecca A. Hutchinson, Li-Ping Liu, Thomas G. Diet...
TSMC
2008
117views more  TSMC 2008»
14 years 8 months ago
Discovery of High-Level Behavior From Observation of Human Performance in a Strategic Game
This paper explores the issues faced in creating a sys-4 tem that can learn tactical human behavior merely by observing5 a human perform the behavior in a simulation. More specific...
Brian S. Stensrud, Avelino J. Gonzalez
IUI
2010
ACM
15 years 6 months ago
Agent-assisted task management that reduces email overload
RADAR is a multiagent system with a mixed-initiative user interface designed to help office workers cope with email overload. RADAR agents observe experts to learn models of their...
Aaron Steinfeld, Andrew Faulring, Asim Smailagic, ...