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» A cognitive framework for imitation learning
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NIPS
2007
14 years 11 months ago
The Tradeoffs of Large Scale Learning
This contribution develops a theoretical framework that takes into account the effect of approximate optimization on learning algorithms. The analysis shows distinct tradeoffs for...
Léon Bottou, Olivier Bousquet
SPIESR
2001
160views Database» more  SPIESR 2001»
14 years 11 months ago
New frontiers for intelligent content-based retrieval
In this paper, we examine emerging frontiers in the evolution of content-based retrieval systems that rely on an intelligent infrastructure. Here, we refer to intelligence as the ...
Ana B. Benitez, John R. Smith
AIED
2009
Springer
15 years 4 months ago
Modeling Task-Based vs. Affect-based Feedback Behavior in Pedagogical Agents: An Inductive Approach
Affect has been the subject of increasing attention in cognitive accounts of learning. Many intelligent tutoring systems now seek to adapt pedagogy to student affective and motivat...
Jennifer L. Robison, Scott W. McQuiggan, James C. ...
SMC
2007
IEEE
102views Control Systems» more  SMC 2007»
15 years 3 months ago
An improved immune Q-learning algorithm
—Reinforcement learning is a framework in which an agent can learn behavior without knowledge on a task or an environment by exploration and exploitation. Striking a balance betw...
Zhengqiao Ji, Q. M. Jonathan Wu, Maher A. Sid-Ahme...
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ATAL
2009
Springer
15 years 4 months ago
Bounded rationality via recursion
Current trends in model construction in the field of agentbased computational economics base behavior of agents on either game theoretic procedures (e.g. belief learning, fictit...
Maciej Latek, Robert L. Axtell, Bogumil Kaminski