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ATAL
2009
Springer
14 years 2 months ago
Generalized model learning for reinforcement learning in factored domains
Improving the sample efficiency of reinforcement learning algorithms to scale up to larger and more realistic domains is a current research challenge in machine learning. Model-ba...
Todd Hester, Peter Stone
AGENTS
1998
Springer
13 years 12 months ago
Learning Situation-Dependent Costs: Improving Planning from Probabilistic Robot Execution
Physical domains are notoriously hard to model completely and correctly, especially to capture the dynamics of the environment. Moreover, since environments change, it is even mor...
Karen Zita Haigh, Manuela M. Veloso
BMCBI
2007
130views more  BMCBI 2007»
13 years 7 months ago
A model-based optimization framework for the inference of regulatory interactions using time-course DNA microarray expression da
Background: Proteins are the primary regulatory agents of transcription even though mRNA expression data alone, from systems like DNA microarrays, are widely used. In addition, th...
Reuben Thomas, Carlos J. Paredes, Sanjay Mehrotra,...
BMCBI
2004
323views more  BMCBI 2004»
13 years 7 months ago
Biochemical Network Stochastic Simulator (BioNetS): software for stochastic modeling of biochemical networks
Background: Intrinsic fluctuations due to the stochastic nature of biochemical reactions can have large effects on the response of biochemical networks. This is particularly true ...
David Adalsteinsson, David McMillen, Timothy C. El...
KI
2010
Springer
13 years 5 months ago
A Testbed for Adaptive Human-Robot Collaboration
Abstract. This paper presents a novel method for developing and evaluating intelligent robot behavior for joint human-robot activities. We extended a physical simulation of an auto...
Alexandra Kirsch, Yuxiang Chen