Cognitive Attraction Theory and Moral Judgment

Abstract

The present article deals with the processes that underpin moral judgment. In the specialized literature, some concepts are proven to be important mechanisms that build up the moral judgment. For instance, intuition, emotion, reasoning, moral rules, deontology and consequentialism. However, there is a lack of a comprehensive framework, which puts together those key concepts in a clear picture. The present article argues for a more comprehensive view under the light of the Cognitive Attraction Theory (CAT). The derived framework considers emotion as the main facilitator of moral judgment as it acts as the means of conceptual attraction between the different cognitive entities, including moral beliefs and rules. Based on this principle, we show how the moral judgment "evolves" from a moral intuition, sometimes endorsed by a reasoning fallacy, to an elaborated judgment that is a result of a conscious reasoning. With the help of a computer simulation performed with an artificial moral agent that incarnates a computational model of CAT, we show that moral judgment can be deontological or consequentialistic.

A Cognitive Attraction Network Approach to the Software Team Building Decision Problem

“…We use these formulation elements to construct a Cognitive Attraction Network (CAN). CAN was introduced in [30][31]. Figure 1 depicts the developer assignment problem's CAN with a single task.…”

Design and evaluation of a cognitive system to teach software change control

“…The automation of the software change control decision relies on a cognitive software agent, which simulates the reasoning processes of the CCB members. The agent's design uses a Cognitive Attraction Network (CAN), which is an adaptation of the formalism introduced by . A software change decision CAN contains a set of goals G i , i = 1, 2, …, n, a set of facts F j , j = 1, 2, …, m, and a set of possible software change actions A k , k = 1, 2, …, p. These goals, facts, and actions are subsets of those listed above, chosen to reflect the real components and aspects of the software project under hands.…”

“…The automation of the software change control decision relies on a cognitive software agent, which simulates the reasoning processes of the CCB members. The agent's design uses a Cognitive Attraction Network (CAN), which is an adaptation of the formalism introduced by [38]. A software change decision CAN contains a set of goals G i , i ¼ 1, 2, .…”

Fuzzy and Cognitive Attraction Based Solution for the Software Architectural Change Decision Problem

“…As conjectured by CAT, mental associations are the emergence of the Hebb's rule and they convey cognitive attractions. Based on this conjecture, CAT has been used in [35] to elaborate a moral decision algorithm, where moral goals cognitively attract moral decisions through the conceptual links that exist between every moral decision and the relevant moral goal. Such an attraction is numerically weighted by the empirical plausibility degree that expresses the extent to which the subject believes that the moral decision causes the fulfillment of the moral goal.…”

“…This phase of the proposed architectural change decision algorithm relies on the Cognitive Attraction Theory (CAT) [34,35]. The latter underlines the ontological and epistemological (onto-epistemological) mechanisms that make human cognition emerge from neuronal dynamics.…”