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ECAI
2010
Springer
13 years 12 months ago
The Dynamics of Multi-Agent Reinforcement Learning
Abstract. Infinite-horizon multi-agent control processes with nondeterminism and partial state knowledge have particularly interesting properties with respect to adaptive control, ...
Luke Dickens, Krysia Broda, Alessandra Russo
NEUROSCIENCE
2001
Springer
14 years 3 months ago
Analysis and Synthesis of Agents That Learn from Distributed Dynamic Data Sources
We propose a theoretical framework for specification and analysis of a class of learning problems that arise in open-ended environments that contain multiple, distributed, dynamic...
Doina Caragea, Adrian Silvescu, Vasant Honavar

Publication
154views
13 years 1 months ago
Preference elicitation and inverse reinforcement learning
We state the problem of inverse reinforcement learning in terms of preference elicitation, resulting in a principled (Bayesian) statistical formulation. This generalises previous w...
Constantin Rothkopf, Christos Dimitrakakis
FLAIRS
2004
14 years 8 days ago
Automatic Creation of Contextual Knowledge in Simulated Agents
Modeling human behavior can be complicated and expensive. To be able to reduce costs, new methodologies and tools must be developed that automate the creation of human behavior mo...
Hans Fernlund, Avelino J. Gonzalez
CORR
2007
Springer
73views Education» more  CORR 2007»
13 years 11 months ago
Universal Reinforcement Learning
—We consider an agent interacting with an unmodeled environment. At each time, the agent makes an observation, takes an action, and incurs a cost. Its actions can influence futu...
Vivek F. Farias, Ciamac Cyrus Moallemi, Tsachy Wei...