The links between genetic algorithms and population-based Markov Chain Monte Carlo (MCMC) methods are explored. Genetic algorithms (GAs) are well-known for their capability to opt...
A novel method, for solving satisfiability (SAT) instances is presented. It is based on two components: a) An Epistasis Reducer Algorithm (ERA) that produces a more suited represe...
PPP is a Web-based simulation and synthesis environment for low-power design. In this paper we describe the gate-level simulation engine of PPP, that achieves accuracy always with...
Alessandro Bogliolo, Luca Benini, Bruno Ricc&ograv...
Exponential increases in architectural design complexity threaten to make traditional processor design optimization techniques intractable. Genetically programmed response surface...
We present an experimental comparison of different genetic operators regarding their use in an evolutionary learning method that searches for unwanted emergent behavior in a multi...