Cooperative Co-evolution Inspired Operators for Classical GP Schemes

Threshold Selection, Mitosis and Dual Mutation in Cooperative Co-evolution: Application to Medical 3D Tomography

We present and analyse the behaviour of specialised operators designed for cooperative coevolution strategy in the framework of 3D tomographic PET reconstruction. The basis is a simple cooperative co-evolution scheme (the “fly algorithm”), which embeds the searched solution in the whole population, letting each individual be only a part of the solution. An individual, or fly, is a 3D point that...

Cooperative Co-Evolving Neural Networks for Robosoccer Simulation

Assessment of Rural Households Participation in Cooperative Societies and Agricultural Activities in Delta State, Nigeria

The primary objective of this research is to examine the contributions of co-operatives on rural household agricultural productivity. Multistage sampling was employed in the random selection of 120 co-operators and non-cooperators respectively. But only 115 co-operators and non-cooperators were utilized for the study. The active mean age of 42 years and married female rural households with seco...

Programming with Annotated Grammar Estimation

Evolutionary algorithms (EAs) mimic natural evolution to solve optimization problems. Because EAs do not require detailed assumptions, they can be applied to many real-world problems. In EAs, solution candidates are evolved using genetic operators such as crossover and mutation which are analogs to natural evolution. In recent years, EAs have been considered from the viewpoint of distribution e...

Cooperative Behavior Acquisition in a Multiple Mobile Robot Environment by Co-evolution

Co-evolution has been receiving increased attention as a method for multi agent simultaneous learning. This paper discusses how multiple robots can emerge cooperative behaviors through co-evolutionary processes. As an example task, a simpli ed soccer game with three learning robots is selected and a GP (genetic programming) method is applied to individual population corresponding to each robot ...