Belief Revision by Lamarckian Evolution

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 t...

{ ? 1 Belief Revision by Multi - Agent Genetic

The revision of beliefs is an important general purpose functionality that an agent must exhibit. The agent usually needs to perform this task in cooperation with other agents, because access to knowledge and the knowledge itself are distributed in nature. In this work, we propose a new approach for performing belief revision in a society of logic-based agents, by means of a (distributed) genet...

Belief Revision via Lamar kian Evolution 1 Belief Revision via Lamar kian

Iterated Belief Change: A Transition System Approach

We use a transition system approach to reason about the evolution of an agent’s beliefs as actions are executed. Some actions cause an agent to perform belief revision and some actions cause an agent to perform belief update, but the interaction between revision and update can be nonelementary. We present a set of basic postulates describing the interaction of revision and update, and we introd...

A Lamarckian Evolution Strategy for Genetic Algorithms

A Prolog implementation of a simple Lamarckian evolution module for genetic algorithms is discussed. Lamarckian evolution posits that characteristics acquired during a phenotype's lifetime may be inherited by offspring. Although largely dismissed as a viable evolutionary theory for natural systems, Lamarckian evolution has proven effective within computer applications. The strengths of the impl...