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CI
2002
92views more  CI 2002»
14 years 11 months ago
Model Selection in an Information Economy: Choosing What to Learn
As online markets for the exchange of goods and services become more common, the study of markets composed at least in part of autonomous agents has taken on increasing importance...
Christopher H. Brooks, Robert S. Gazzale, Rajarshi...
ICML
2005
IEEE
16 years 19 days ago
Active learning for Hidden Markov Models: objective functions and algorithms
Hidden Markov Models (HMMs) model sequential data in many fields such as text/speech processing and biosignal analysis. Active learning algorithms learn faster and/or better by cl...
Brigham Anderson, Andrew Moore
ACOM
2004
Springer
15 years 5 months ago
Optimal Communication Vocabularies and Heterogeneous Ontologies
In this paper, we will consider the alignment of heterogeneous ontologies in multi agent systems. We will start from the idea that each individual agent is specialized in solving ...
Jurriaan van Diggelen, Robbert-Jan Beun, Frank Dig...
ICRA
2010
IEEE
148views Robotics» more  ICRA 2010»
14 years 10 months ago
Body schema acquisition through active learning
— We present an active learning algorithm for the problem of body schema learning, i.e. estimating a kinematic model of a serial robot. The learning process is done online using ...
Ruben Martinez-Cantin, Manuel Lopes, Luis Montesan...
ATAL
2011
Springer
13 years 11 months ago
Metric learning for reinforcement learning agents
A key component of any reinforcement learning algorithm is the underlying representation used by the agent. While reinforcement learning (RL) agents have typically relied on hand-...
Matthew E. Taylor, Brian Kulis, Fei Sha