Realizing an optimization approach inspired from Piagets theory on cognitive development

TL;DR

This paper introduces CoDOA, an AI-based optimization algorithm inspired by Piaget's cognitive development theory, employing swarm intelligence to address single-objective optimization problems with promising initial results.

Contribution

The paper presents a novel optimization algorithm, CoDOA, inspired by Piaget's cognitive development theory, integrating cognitive process modeling into swarm intelligence for optimization.

Findings

Effective on benchmark functions

Potential as an alternative optimization method

Initial promising results

Abstract

The objective of this paper is to introduce an artificial intelligence based optimization approach, which is inspired from Piagets theory on cognitive development. The approach has been designed according to essential processes that an individual may experience while learning something new or improving his / her knowledge. These processes are associated with the Piagets ideas on an individuals cognitive development. The approach expressed in this paper is a simple algorithm employing swarm intelligence oriented tasks in order to overcome single-objective optimization problems. For evaluating effectiveness of this early version of the algorithm, test operations have been done via some benchmark functions. The obtained results show that the approach / algorithm can be an alternative to the literature in terms of single-objective optimization. The authors have suggested the name: Cognitive Development Optimization Algorithm (CoDOA) for the related intelligent optimization approach.