Logic aided Lamarckian evolution

We propose a multi-strategy genetic algorithm for performing belief revision. The algorithm implements a new evolutionary strategy which is a combination of the theories of Darwin and Lamarck. Therefore, the algorithm not only includes the Darwinian operators of selection, mutation and crossover but also a Lamarckian operator that changes the individuals so that they perform better in solving the given problem. This is achieved through belief revision directed mutations, oriented by tracing logical derivations. The algorithm, with and without the Lamarckian operator, is tested on a number of belief revision problems, and the results show that the addition of the Lamarckian operator improves the eciency of the algorithm. We believe that the combination of Darwinian and Lamarckian operators will be useful not only for standard belief revision problems but especially for problems where the chromosomes may be exposed to dierent constraints and observations. In these cases, the Lamarckian and Darwinian operators would play a dierent role: the Lamarckian one would be used in order to bring a chromosome closer to a solution or to nd an exact solution of the current belief revision problem, while Darwinian ones will have the aim of preparing chromosomes to deal with new situations by exchanging genes among them.