We have studied the adaptation of mutation rates in a simple model of evolution. The model consists of a two-dimensional world with a periodically replenished resource and a uctuating population of evolving agents whose survival and reproduction are an implicit a function of their success at nding resources and their internal metabolism. Earlier work suggested that mutation rate is a control pa...

Acquisition of resistance secondary to treatment both by microorganisms and by tumor cells is a major public health concern. Several species of bacteria acquire resistance to various antibiotics through stress-induced responses that have an adaptive mutagenesis effect. So far, adaptive mutagenesis in yeast has only been described when the stress is nutrient deprivation. Here, we hypothesized th...

A major problem with the Artificial Bee Colony (ABC) algorithm is its premature convergence to the locally optimal points of the search space, which often originates from the lack of explorative search capability of its mutation operator. This paper introduces ABC with Adaptive Mutation Rate (ABC-AMR), a novel algorithm that modifies the basic mutation operation of the original ABC algorithm in...

The particle swarm optimization (PSO) is a wide used algorithm, which yet suffers from trapping in local optimum and the premature convergence. Many studies have proposed improvements to address drawbacks above. Most of them implemented single strategy for one problem or fixed neighborhood structure during whole search process. To further improve PSO performance, we introduced simple but effect...

The cells in most tumors are found to carry multiple mutations; however, based upon mutation rates determined by fluctuation tests, the frequency of such multiple mutations should be so low that tumors are never detected within human populations. Fluctuation tests, which determine the cell-division-dependent mutation rate per cell generation in growing cells, may not be appropriate for estimati...