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NIPS
2004
15 years 7 months ago
Learning first-order Markov models for control
First-order Markov models have been successfully applied to many problems, for example in modeling sequential data using Markov chains, and modeling control problems using the Mar...
Pieter Abbeel, Andrew Y. Ng
NIPS
2004
15 years 7 months ago
New Criteria and a New Algorithm for Learning in Multi-Agent Systems
We propose a new set of criteria for learning algorithms in multi-agent systems, one that is more stringent and (we argue) better justified than previous proposed criteria. Our cr...
Rob Powers, Yoav Shoham
UAI
2001
15 years 7 months ago
Aggregating Learned Probabilistic Beliefs
We consider the task of aggregating beliefs of several experts. We assume that these beliefs are represented as probability distributions. We argue that the evaluation of any aggr...
Pedrito Maynard-Reid II, Urszula Chajewska
IJCAI
2003
15 years 7 months ago
When Discriminative Learning of Bayesian Network Parameters Is Easy
Bayesian network models are widely used for discriminative prediction tasks such as classification. Usually their parameters are determined using 'unsupervised' methods ...
Hannes Wettig, Peter Grünwald, Teemu Roos, Pe...
ICML
2010
IEEE
15 years 7 months ago
Nonparametric Return Distribution Approximation for Reinforcement Learning
Standard Reinforcement Learning (RL) aims to optimize decision-making rules in terms of the expected return. However, especially for risk-management purposes, other criteria such ...
Tetsuro Morimura, Masashi Sugiyama, Hisashi Kashim...