A Review of 40 Years of Cognitive Architecture Research: Core Cognitive Abilities and Practical Applications

TL;DR

This comprehensive review covers 40 years of cognitive architecture research, highlighting core cognitive abilities, practical applications, and recent trends across nearly 85 architectures and 900 projects, emphasizing diversity and ongoing development.

Contribution

It provides an inclusive, high-level overview of cognitive architectures, focusing on core abilities and practical applications, and introduces visualization of field-wide development trends.

Findings

49 architectures are actively developed

Over 900 practical projects implemented

Diverse disciplines influence current architectures

Abstract

In this paper we present a broad overview of the last 40 years of research on cognitive architectures. Although the number of existing architectures is nearing several hundred, most of the existing surveys do not reflect this growth and focus on a handful of well-established architectures. Thus, in this survey we wanted to shift the focus towards a more inclusive and high-level overview of the research on cognitive architectures. Our final set of 84 architectures includes 49 that are still actively developed, and borrow from a diverse set of disciplines, spanning areas from psychoanalysis to neuroscience. To keep the length of this paper within reasonable limits we discuss only the core cognitive abilities, such as perception, attention mechanisms, action selection, memory, learning and reasoning. In order to assess the breadth of practical applications of cognitive architectures we gathered information on over 900 practical projects implemented using the cognitive architectures in our list. We use various visualization techniques to highlight overall trends in the development of the field. In addition to summarizing the current state-of-the-art in the cognitive architecture research, this survey describes a variety of methods and ideas that have been tried and their relative success in modeling human cognitive abilities, as well as which aspects of cognitive behavior need more research with respect to their mechanistic counterparts and thus can further inform how cognitive science might progress.