- Full text PDF available (8)
The phenomenon of preadaptation, or exaptation (wherein a trait that originally evolved to solve one problem is co-opted to solve a new problem) presents a formidable challenge to efforts to describe biological phenomena using a classical (Kolmogorovian) mathematical framework. We develop a quantum framework for exaptation with examples from both biological… (More)
In many applications of evolutionary algorithms, the time required to evaluate the fitness of individuals is long and variable. When the variance in individual evaluation times is non-negligible, traditional, synchronous master-slave EAs incur idle time in CPU resources. An asynchronous approach to parallelization of EAs promises to eliminate idle time and… (More)
Applying evolutionary algorithms to new problem domains is an exercise in the art of parameter tuning and design decisions. A great deal of work has investigated ways to automate the tuning of various EA parameters such as population size, mutation options, etc. However, genotype-to-phenotype mappings have typically been considered too complex to adapt… (More)
Parallelization of fitness evaluation is an established practice in evolutionary computation, and is a necessity in applications where fitness functions are computationally expensive. Traditional master-slave EAs based on a synchronous, generational model incur idle time when there is variance in the time it takes for individuals to have their fitness… (More)
Attorneys across the United States use government-provided electronic databases to submit docket entries and associated case files for processing and archival in public judicial records. Data entry errors in these repositories, while rare, can disrupt the court process, confuse the public record, or breach privacy and confidentiality. Docket quality… (More)
A number of papers have emerged in the last two years that apply and study asynchronous master-slave evolutionary algorithms based on a steady-state model. These efforts are largely motivated by the observation that, unlike traditional (synchronous) EAs, asynchronous EAs are able to make maximal use of many parallel processors, even when some individuals… (More)
We introduce a genetic programming method for solving multiple Boolean circuit synthesis tasks simultaneously. This allows us to solve a set of elementary logic functions twice as easily as with a direct, single-task approach.