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» Solving identification problem for asynchronous finite state...
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VTS
1998
IEEE
97views Hardware» more  VTS 1998»
13 years 10 months ago
On the Identification of Optimal Cellular Automata for Built-In Self-Test of Sequential Circuits
This paper presents a BIST architecture for Finite State Machines that exploits Cellular Automata (CA) as pattern generators and signature analyzers. The main advantage of the pro...
Fulvio Corno, Nicola Gaudenzi, Paolo Prinetto, Mat...
ICML
1996
IEEE
13 years 9 months ago
A Convergent Reinforcement Learning Algorithm in the Continuous Case: The Finite-Element Reinforcement Learning
This paper presents a direct reinforcement learning algorithm, called Finite-Element Reinforcement Learning, in the continuous case, i.e. continuous state-space and time. The eval...
Rémi Munos
GECCO
2009
Springer
156views Optimization» more  GECCO 2009»
14 years 6 days ago
Characterizing the genetic programming environment for fifth (GPE5) on a high performance computing cluster
Solving complex, real-world problems with genetic programming (GP) can require extensive computing resources. However, the highly parallel nature of GP facilitates using a large n...
Kenneth Holladay
ICCAD
1997
IEEE
126views Hardware» more  ICCAD 1997»
13 years 9 months ago
An output encoding problem and a solution technique
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...
Subhasish Mitra, LaNae J. Avra, Edward J. McCluske...
CDC
2010
IEEE
139views Control Systems» more  CDC 2010»
13 years 19 days ago
Q-learning and enhanced policy iteration in discounted dynamic programming
We consider the classical finite-state discounted Markovian decision problem, and we introduce a new policy iteration-like algorithm for finding the optimal state costs or Q-facto...
Dimitri P. Bertsekas, Huizhen Yu