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» Compositional Models for Reinforcement Learning
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ATAL
2008
Springer
13 years 9 months ago
Artificial agents learning human fairness
Recent advances in technology allow multi-agent systems to be deployed in cooperation with or as a service for humans. Typically, those systems are designed assuming individually ...
Steven de Jong, Karl Tuyls, Katja Verbeeck
ACL
2012
11 years 10 months ago
Learning High-Level Planning from Text
Comprehending action preconditions and effects is an essential step in modeling the dynamics of the world. In this paper, we express the semantics of precondition relations extrac...
S. R. K. Branavan, Nate Kushman, Tao Lei, Regina B...
JMLR
2008
141views more  JMLR 2008»
13 years 7 months ago
Accelerated Neural Evolution through Cooperatively Coevolved Synapses
Many complex control problems require sophisticated solutions that are not amenable to traditional controller design. Not only is it difficult to model real world systems, but oft...
Faustino J. Gomez, Jürgen Schmidhuber, Risto ...
JMLR
2010
119views more  JMLR 2010»
13 years 2 months ago
A Convergent Online Single Time Scale Actor Critic Algorithm
Actor-Critic based approaches were among the first to address reinforcement learning in a general setting. Recently, these algorithms have gained renewed interest due to their gen...
Dotan Di Castro, Ron Meir
ACL
2010
13 years 5 months ago
Learning to Adapt to Unknown Users: Referring Expression Generation in Spoken Dialogue Systems
We present a data-driven approach to learn user-adaptive referring expression generation (REG) policies for spoken dialogue systems. Referring expressions can be difficult to unde...
Srinivasan Janarthanam, Oliver Lemon