Artificial Motivation for Cognitive Software Agents

Ryan J. McCall; Stan Franklin; Usef Faghihi; Javier Snaider; Sean Kugele

doi:10.2478/jagi-2020-0002

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Artificial Motivation for Cognitive Software Agents

Journal of Artificial General Intelligence

Volume 11 (2020): Issue 1 (January 2020)

By: Ryan J. McCall, Stan Franklin, Usef Faghihi, Javier Snaider and Sean Kugele

Open Access

|Feb 2020

Abstract

Natural selection has imbued biological agents with motivations moving them to act for survival and reproduction, as well as to learn so as to support both. Artificial agents also require motivations to act in a goal-directed manner and to learn appropriately into various memories. Here we present a biologically inspired motivation system, based on feelings (including emotions) integrated within the LIDA cognitive architecture at a fundamental level. This motivational system, operating within LIDA’s cognitive cycle, provides a repertoire of motivational capacities operating over a range of time scales of increasing complexity. These include alarms, appraisal mechanisms, appetence and aversion, and deliberation and planning.

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Articles in this issue

DOI: https://doi.org/10.2478/jagi-2020-0002 | Journal eISSN: 1946-0163

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Language: English

Page range: 38 - 69

Submitted on: Jan 20, 2017

Accepted on: Dec 24, 2019

Published on: Feb 1, 2020

Published by: Artificial General Intelligence Society

In partnership with: Paradigm Publishing Services

Publication frequency: 2 issues per year

Keywords:

Artificial Motivation,

Emotion,

LIDA

Related subjects:

Computer sciences,

Artificial intelligence

© 2020 Ryan J. McCall, Stan Franklin, Usef Faghihi, Javier Snaider, Sean Kugele, published by Artificial General Intelligence Society
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Volume 11 (2020): Issue 1 (January 2020)