Improving the Survival Time of Multiagents in Social Dilemmas through Neurotransmitter-Based Deep Q-Learning Model of Emotions.
Journal
Journal of healthcare engineering
ISSN: 2040-2309
Titre abrégé: J Healthc Eng
Pays: England
ID NLM: 101528166
Informations de publication
Date de publication:
2022
2022
Historique:
received:
08
10
2021
accepted:
28
12
2021
entrez:
7
2
2022
pubmed:
8
2
2022
medline:
3
5
2022
Statut:
epublish
Résumé
In multiagent systems, social dilemmas often arise whenever there is a competition over the limited resources. The major challenge is to establish cooperation among intelligent virtual agents for solving the situations of social dilemmas. In humans, personality and emotions are the primary factors that lead them toward a cooperative environment. To make agents cooperate, they have to become more like humans, that is, believable. Therefore, we hypothesize that emotions according to the personality give birth to believability, and if believability is introduced into agents through emotions, it improves their survival rate in social dilemma situations. The existing researches have introduced different computational models to introduce emotions in virtual agents, but they lack emotions through neurotransmitters. We have proposed a neurotransmitters-based deep Q-learning computational model in multiagents that is a suitable choice for emotion modeling and, hence, believability. The proposed model regulates the agents' emotions by controlling the virtual neurotransmitters (dopamine and oxytocin) according to the agent's personality. The personality of the agent is introduced using OCEAN model. To evaluate the proposed system, we simulated a survival scenario with limited food resources in different experiments. These experiments vary the number of selfish agents (higher neuroticism personality trait) and the selfless agents (higher agreeableness personality trait). Experimental results show that by adding the selfless agents in the scenario, the agents develop cooperation, and their collective survival time increases. Thus, to resolve the social dilemma problems in virtual agents, we can make agents believable through the proposed neurotransmitter-based emotional model. This proposed work may help in developing nonplayer characters (NPCs) in games.
Identifiants
pubmed: 35126919
doi: 10.1155/2022/3449433
pmc: PMC8808197
doi:
Substances chimiques
Neurotransmitter Agents
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
3449433Informations de copyright
Copyright © 2022 Awais Hassan et al.
Déclaration de conflit d'intérêts
The authors declare that they have no conflicts of interest.
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