Hybridization of cognitive models using evolutionary strategies

Abstract

Incorporating different kinds of micro-theories of cognition and modulating several mechanisms to unify all the recommended actions and outputs of an Intelligent System when a huge amount of environmental variables are changing continuously with increasing complexity, may become a very comprehensive task. The presented framework proposes an Hybrid Cognitive Architecture that relies on integrating of emergent systems approaches —connectionist and autopoietic systems—, and cognitivist approaches, in order to combine implicit and explicit processes necessary in developing cognitive skills. The proposed architecture includes different kinds of learning capabilities at each cognitive level which grant to the architecture a big plasticity. In addition, the propounded attention module includes an evolutionary mechanism based on gene expression programming to evolve a set of eligibility conditions in charge of modulating the coalition/ subordination of specialized behaviours, taking into consideration the theatre metaphor for consciousness. Finally, a co-evolutionary mechanism is proposed to propagate behaviours and knowledge between cognitive systems —Agents— on the basis of memetic engineering. The proposed architecture was proved in an animat environment using a multi-agent platform where several emergent properties of self-organization arose.