Abstract. Parallel genetic algorithms are usually implemented on parallel machines or distributed systems. This paper describes how finegrained parallel genetic algorithms can be ...
We introduce a genetic programming (GP) approach for evolving genetic networks that demonstrate desired dynamics when simulated as a discrete stochastic process. Our representation...
Withthe advent of the HumanGenomeProject. the ability to rapidly construct comprehensiveand accuratelinkage mapsbasedongenetic markerdata fromfamily studies is an absolute necessi...
Tara Cox Matise, Mark Perlin, Aravinda Chakravarti
A new stochastic method for locating the global minimum of a multidimensional function inside a rectangular hyperbox is presented. A sampling technique is employed that makes use ...
Interaction programming bridges the gap between interaction design and programming, but it has not yet been related directly to mainstream development practice. This paper present...