Evolution of Ideas: A Novel Memetic Algorithm Based on Semantic Networks

TL;DR

This paper introduces a novel memetic algorithm that evolves semantic networks representing knowledge, using analogy-based fitness measures and knowledge bases, to model memetic theories of cultural evolution.

Contribution

It presents a new memetic algorithm based on semantic networks and analogy-based fitness, differing from traditional memetic algorithms by evolving units of culture.

Findings

Demonstrates the feasibility of evolving semantic networks with memetic operators.

Uses analogy-based fitness to guide evolution towards knowledge structures.

Provides a computational tool for modeling memetic and cultural evolution theories.

Abstract

This paper presents a new type of evolutionary algorithm (EA) based on the concept of "meme", where the individuals forming the population are represented by semantic networks and the fitness measure is defined as a function of the represented knowledge. Our work can be classified as a novel memetic algorithm (MA), given that (1) it is the units of culture, or information, that are undergoing variation, transmission, and selection, very close to the original sense of memetics as it was introduced by Dawkins; and (2) this is different from existing MA, where the idea of memetics has been utilized as a means of local refinement by individual learning after classical global sampling of EA. The individual pieces of information are represented as simple semantic networks that are directed graphs of concepts and binary relations, going through variation by memetic versions of operators such as crossover and mutation, which utilize knowledge from commonsense knowledge bases. In evaluating this introductory work, as an interesting fitness measure, we focus on using the structure mapping theory of analogical reasoning from psychology to evolve pieces of information that are analogous to a given base information. Considering other possible fitness measures, the proposed representation and algorithm can serve as a computational tool for modeling memetic theories of knowledge, such as evolutionary epistemology and cultural selection theory.