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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...
CAEPIA
2011
Springer
12 years 11 months ago
Evaluating a Reinforcement Learning Algorithm with a General Intelligence Test
In this paper we apply the recent notion of anytime universal intelligence tests to the evaluation of a popular reinforcement learning algorithm, Q-learning. We show that a general...
Javier Insa-Cabrera, David L. Dowe, José He...
AGI
2011
13 years 2 months ago
Reinforcement Learning and the Bayesian Control Rule
We present an actor-critic scheme for reinforcement learning in complex domains. The main contribution is to show that planning and I/O dynamics can be separated such that an intra...
Pedro Alejandro Ortega, Daniel Alexander Braun, Si...
ICML
2004
IEEE
14 years 11 months ago
Using relative novelty to identify useful temporal abstractions in reinforcement learning
lative Novelty to Identify Useful Temporal Abstractions in Reinforcement Learning ?Ozg?ur S?im?sek ozgur@cs.umass.edu Andrew G. Barto barto@cs.umass.edu Department of Computer Scie...
Özgür Simsek, Andrew G. Barto
JSW
2007
112views more  JSW 2007»
13 years 10 months ago
The Challenge of Training New Architects: an Ontological and Reinforcement-Learning Methodology
— This paper describes the importance of new skilled architects in the discipline of Software and Enterprise Architecture. Architects are often idealized as super heroes with a l...
Anabel Fraga, Juan Lloréns