AHA: A general cognitive architecture for Darwinian agents

Authored by Jarl Giske, Sergey Budaev, Sigrunn Eliassen

Date Published: 2018

DOI: 10.1016/j.bica.2018.07.009

Sponsors: No sponsors listed

Platforms: Fortran

Model Documentation: Other Narrative Flow charts

Model Code URLs: https://github.com/sbudaev/AHA-R1

Abstract

Unified theories of cognition have traditionally played a vital role in understanding the human mind. In the animal behavior field, however, acceptance of holistic views on the behavioral phenotype that includes diverse cognitive and behavioral traits is rather slow. Studying adaptation and evolution of behavior, especially complex cognition and decision making, requires integrative models applicable to a range of species. We describe a general cognitive architecture and a modeling framework for studying evolution and adaptation of behavior and cognition that we call Adapted Heuristics and Architecture (AHA). AHA is non-symbolic, rule-based and grounded in general neurobiological mechanisms. It integrates the whole organism with its genome, physiology, hormones, perception, emotion, motivation and cognition in an agent based model environment. The method lets us investigate various scenarios for the evolution of cognition, decision making and emergence of subjective phenomena. We illustrate the potential feasibility of the framework with a model of simple forms of self-awareness.

Tags

Evolution Decision-Making ecology Model emotion foraging theory Energy consciousness evolutionary Experience Genetic algorithm Behavioral ecology Individual-differences Cognitive architecture Ethology Proximate architecture