2467 search results - page 291 / 494 » Finite State Machines |
177
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ICML
2005
IEEE
16 years 7 months ago
2005
IEEE
We consider reinforcement learning in systems with unknown dynamics. Algorithms such as E3 (Kearns and Singh, 2002) learn near-optimal policies by using "exploration policies...
181
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ICML
2005
IEEE
16 years 7 months ago
2005
IEEE
The conditional distribution of a discrete variable y, given another discrete variable x, is often specified by assigning one multinomial distribution to each state of x. The cost...
132
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ICML
2004
IEEE
16 years 7 months ago
2004
IEEE
We present a trainable sequential-inference technique for processes with large state and observation spaces and relational structure. Our method assumes "reliable observation...
151
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ICML
2003
IEEE
16 years 7 months ago
2003
IEEE
Hierarchical reinforcement learning is a general framework which attempts to accelerate policy learning in large domains. On the other hand, policy gradient reinforcement learning...
196
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ICML
2000
IEEE
16 years 7 months ago
2000
IEEE
Hidden Markov models (HMMs) are a powerful probabilistic tool for modeling sequential data, and have been applied with success to many text-related tasks, such as part-of-speech t...