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NIPS
2000
15 years 3 months ago
Programmable Reinforcement Learning Agents
We present an expressive agent design language for reinforcement learning that allows the user to constrain the policies considered by the learning process.The language includes s...
David Andre, Stuart J. Russell
TSMC
2002
143views more  TSMC 2002»
15 years 2 months ago
Robot visual servoing with iterative learning control
Abstract--This paper presents an iterative learning scheme for visionguided robot trajectory tracking. At first, a stability criterion for designing iterative learning controller i...
Ping Jiang, Rolf Unbehauen
CEAS
2006
Springer
15 years 6 months ago
Fast Uncertainty Sampling for Labeling Large E-mail Corpora
One of the biggest challenges in building effective anti-spam solutions is designing systems to defend against the everevolving bag of tricks spammers use to defeat them. Because ...
Richard Segal, Ted Markowitz, William Arnold
ICALT
2007
IEEE
15 years 8 months ago
Towards Advanced Learner Modeling: Discussions on Quasi Real-time Adaptation with Physiological Data
In this paper, we discuss the use of physiological data for quasi real-time adaptation in ITS. We present preliminary results where we analyze learners’ reactions while using a ...
Emmanuel G. Blanchard, Pierre Chalfoun, Claude Fra...
IWLCS
2000
Springer
15 years 6 months ago
Strength and Money: An LCS Approach to Increasing Returns
This paper reports on a number of experiments where three different groups of artificial agents learn, forecast and trade their holdings in a real stock market scenario given exoge...
Sonia Schulenburg, Peter Ross