1916 search results - page 181 / 384 » Reconfiguring a state machine |
ICML
2003
IEEE
14 years 9 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...
ICML
2000
IEEE
14 years 9 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...
COLT
2007
Springer
14 years 2 months ago
2007
Springer
The standard so-called experts algorithms are methods for utilizing a given set of “experts” to make good choices in a sequential decision-making problem. In the standard setti...
ICCAD
1997
IEEE
14 years 11 days ago
1997
IEEE
We present a new output encoding problem as follows: Given a specification table, such as a truth table or a finite state machine state table, where some of the outputs are specif...
COLT
1995
Springer
13 years 11 months ago
1995
Springer
We present algorithms for exactly learning unknown environments that can be described by deterministic nite automata. The learner performs a walk on the target automaton, where at...