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» Focus of Attention in Reinforcement Learning
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ICANN
2001
Springer
13 years 12 months ago
Market-Based Reinforcement Learning in Partially Observable Worlds
Unlike traditional reinforcement learning (RL), market-based RL is in principle applicable to worlds described by partially observable Markov Decision Processes (POMDPs), where an ...
Ivo Kwee, Marcus Hutter, Jürgen Schmidhuber
ICSTM
2000
103views Management» more  ICSTM 2000»
13 years 8 months ago
The worst failure: repeated failure to learn
Performance measurement systems based on the principle that "if you can't measure it, you can't manage it" reinforce a short-term culture by focussing on tangi...
Alan C. McLucas
DAGM
2005
Springer
14 years 28 days ago
Goal-Directed Search with a Top-Down Modulated Computational Attention System
In this paper we present VOCUS: a robust computational attention system for goal-directed search. A standard bottom-up architecture is extended by a top-down component, enabling th...
Simone Frintrop, Gerriet Backer, Erich Rome
KCAP
2009
ACM
14 years 1 months ago
Interactively shaping agents via human reinforcement: the TAMER framework
As computational learning agents move into domains that incur real costs (e.g., autonomous driving or financial investment), it will be necessary to learn good policies without n...
W. Bradley Knox, Peter Stone
AAAI
1998
13 years 8 months ago
The Dynamics of Reinforcement Learning in Cooperative Multiagent Systems
Reinforcement learning can provide a robust and natural means for agents to learn how to coordinate their action choices in multiagent systems. We examine some of the factors that...
Caroline Claus, Craig Boutilier