From Affect Theoretical Foundations to Computational Models of Intelligent Affective Agents

Bexy Alfonso,Joaquin Taverner,Vicente Botti,Emilio Vivancos

doi:10.3390/app112210874

Abstract

The links between emotions and rationality have been extensively studied and discussed. Several computational approaches have also been proposed to model these links. However, is it possible to build generic computational approaches and languages so that they can be “adapted” when a specific affective phenomenon is being modeled? Would these approaches be sufficiently and properly grounded? In this work, we want to provide the means for the development of these generic approaches and languages by making a horizontal analysis inspired by philosophical and psychological theories of the main affective phenomena that are traditionally studied. Unfortunately, not all the affective theories can be adapted to be used in computational models; therefore, it is necessary to perform an analysis of the most suitable theories. In this analysis, we identify and classify the main processes and concepts which can be used in a generic affective computational model, and we propose a theoretical framework that includes all these processes and concepts that a model of an affective agent with practical reasoning could use. Our generic theoretical framework supports incremental research whereby future proposals can improve previous ones. This framework also supports the evaluation of the coverage of current computational approaches according to the processes that are modeled and according to the integration of practical reasoning and affect-related issues. This framework is being used in the development of the GenIA3 architecture.

Highlights

The simulation of human-like affective behavior has been a challenge of artificial intelligence (AI) for decades [1]
The development of affective agents needs to be based on the foundations proposed in different areas such as psychology, neuroscience, and behavioral economics
It has been necessary to carry out a detailed analysis to select the most suitable theories for modeling affective agents

Summary

Introduction

The simulation of human-like affective behavior has been a challenge of artificial intelligence (AI) for decades [1]. Computational agents have been provided with the capacity to reason, act proactively, achieve goals, sense, and plan (among others) [5]. We are referring to specific affective states that can be tagged with terms such as “joy”, “sadness”, or “anger”, which are in line with the classification in [10]. Fields such as psychology, neuroscience, and economics have tried to address the influence of personality and emotions in human behavior, with their results correlating with each other and reaching important achievements in several application areas such as education or entertainment [11]. Our view of the relationship between emotions and practical reasoning is in line with what contemporary philosophy proposes [13]

Objectives

Discussion

Conclusion