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» Learning of Agents with Limited Resources
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CI
2002
92views more  CI 2002»
13 years 7 months ago
Model Selection in an Information Economy: Choosing What to Learn
As online markets for the exchange of goods and services become more common, the study of markets composed at least in part of autonomous agents has taken on increasing importance...
Christopher H. Brooks, Robert S. Gazzale, Rajarshi...
AGENTS
1999
Springer
14 years 3 days ago
Team-Partitioned, Opaque-Transition Reinforcement Learning
In this paper, we present a novel multi-agent learning paradigm called team-partitioned, opaque-transition reinforcement learning (TPOT-RL). TPOT-RL introduces the concept of usin...
Peter Stone, Manuela M. Veloso
EUROCOLT
1995
Springer
13 years 11 months ago
The structure of intrinsic complexity of learning
Limiting identification of r.e. indexes for r.e. languages (from a presentation of elements of the language) and limiting identification of programs for computable functions (fr...
Sanjay Jain, Arun Sharma
AAAI
1994
13 years 9 months ago
A Computational Market Model for Distributed Configuration Design
This paper presents a precise market model for a well-defined class of distributed configuration design problems. Given a design problem, the model defines a computational economy...
Michael P. Wellman
ATAL
2008
Springer
13 years 9 months ago
Deployed ARMOR protection: the application of a game theoretic model for security at the Los Angeles International Airport
Security at major locations of economic or political importance is a key concern around the world, particularly given the threat of terrorism. Limited security resources prevent f...
James Pita, Manish Jain, Janusz Marecki, Fernando ...