We present a Kernighan-Lin style local improvement heuristic for genetic algorithms. We analyze the run-time cost of the heuristic. We demonstrate through experiments that the heur...
Biological populations are dynamic in both space and time, that is, the population size of a species fluctuates across their habitats over time. There are rarely any static or fix...
Using a set of model landscapes we examine how different mutation rates affect different search metrics. We show that very universal heuristics, such as 1/N and the error threshol...
Abstract. The standard simulation of a nondeterministic Turing machine (NTM) by a deterministic one essentially searches a large boundeddegree graph whose size is exponential in th...
Subrahmanyam Kalyanasundaram, Richard J. Lipton, K...
Abstract In this paper, we demonstrate that two characteristic properties of mammalian brains emerge when scaling-up modular, cortical structures. Firstly, the glia-toneuron ratio ...