252 search results - page 20 / 51 » Learning Partially Observable Action Models: Efficient Algor... |
127
Voted
CORR
2008
Springer
15 years 2 months ago
2008
Springer
Hidden Markov Models (HMMs) are one of the most fundamental and widely used statistical tools for modeling discrete time series. In general, learning HMMs from data is computation...
133
Voted
ROBOCUP
2007
Springer
15 years 8 months ago
2007
Springer
Reinforcement learning is a paradigm under which an agent seeks to improve its policy by making learning updates based on the experiences it gathers through interaction with the en...
119
Voted
ICML
2009
IEEE
16 years 3 months ago
2009
IEEE
We consider the problem of embedding arbitrary objects (e.g., images, audio, documents) into Euclidean space subject to a partial order over pairwise distances. Partial order cons...
117
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ICTAI
2005
IEEE
15 years 8 months ago
2005
IEEE
Partially Observable Markov Decision Processes (POMDPs) provide a general framework for AI planning, but they lack the structure for representing real world planning problems in a...
125
Voted
NECO
2007
15 years 2 months ago
2007
Learning agents, whether natural or artificial, must update their internal parameters in order to improve their behavior over time. In reinforcement learning, this plasticity is ...