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AGI
2011
14 years 3 months ago
Real-World Limits to Algorithmic Intelligence
Abstract. Recent theories of universal algorithmic intelligence, combined with the view that the world can be completely specified in mathematical terms, have led to claims about ...
Leo Pape, Arthur Kok
ATAL
2004
Springer
15 years 5 months ago
Best-Response Multiagent Learning in Non-Stationary Environments
This paper investigates a relatively new direction in Multiagent Reinforcement Learning. Most multiagent learning techniques focus on Nash equilibria as elements of both the learn...
Michael Weinberg, Jeffrey S. Rosenschein

Publication
240views
13 years 10 months ago
Bayesian multitask inverse reinforcement learning
We generalise the problem of inverse reinforcement learning to multiple tasks, from multiple demonstrations. Each one may represent one expert trying to solve a different task, or ...
Christos Dimitrakakis, Constantin A. Rothkopf
ICML
2005
IEEE
16 years 17 days ago
Learning as search optimization: approximate large margin methods for structured prediction
Mappings to structured output spaces (strings, trees, partitions, etc.) are typically learned using extensions of classification algorithms to simple graphical structures (eg., li...
Daniel Marcu, Hal Daumé III
ECML
2003
Springer
15 years 5 months ago
Combined Optimization of Feature Selection and Algorithm Parameters in Machine Learning of Language
Comparative machine learning experiments have become an important methodology in empirical approaches to natural language processing (i) to investigate which machine learning algor...
Walter Daelemans, Véronique Hoste, Fien De ...