Decision Making guided by Emotion A computational architecture

TL;DR

This paper introduces a computational model where emotional signals rapidly influence slow, precise decision-making processes, inspired by neurobiological insights and implemented via Guided Propagation Networks.

Contribution

It presents a novel architecture integrating emotional and cognitive channels using Guided Propagation Networks, simulating emotional influence on decision-making.

Findings

Emotional cues can anticipate action consequences.

The model demonstrates integrated emotional influences.

Simulation shows effects of accidental all-out emotions.

Abstract

A computational architecture is presented, in which "swift and fuzzy" emotional channels guide a "slow and precise" decision-making channel. Reported neurobiological studies first provide hints on the representation of both emotional and cognitive dimensions across brain structures, mediated by the neuromodulation system. The related model is based on Guided Propagation Networks, the inner flows of which can be guided through modulation. A key-channel of this model grows from a few emotional cues, and is aimed at anticipating the consequences of ongoing possible actions. Current experimental results of a computer simulation show the integrated contribution of several emotional influences, as well as issues of accidental all-out emotions.