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...
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...
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...
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...
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...