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CORR
2007
Springer
73views Education» more  CORR 2007»
13 years 4 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 4 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
12 years 8 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 5 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 4 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