Title
A Computational Study on Emotions and Temperament in Multi-Agent Systems
Abstract
Recent advances in neurosciences and psychology have provided evidence that affective phenomena pervade intelligence at many levels, being inseparable from the cognition- action loop. Perception, attention, memory, learning, decision- making, adaptation, communication and social interaction are some of the aspects influenced by them. This work draws its inspirations from neurobiology, psychophysics and sociology to approach the problem of building autonomous robots capable of interacting with each other and building strategies based on temperamental decision mechanism. Modelling emotions is a relatively recent focus in artificial intelligence and cognitive modelling. Such models can ideally inform our understanding of human behavior. We may see the development of computational models of emotion as a core research focus that will facilitate advances in the large array of computational systems that model, interpret or influence human behavior. We propose a model based on a scalable, flexible and modular approach to emotion which allows runtime evaluation between emotional quality and performance. The results achieved showed that the strategies based on temperamental decision mechanism strongly influence the system performance and there are evident dependency between emotional state of the agents and their temperamental type, as well as the dependency between the team performance and the temperamental configuration of the team members, and this enable us to conclude that the modular approach to emotional programming based on temperamental theory is the good choice to develop computational mind models for emotional behavioral Multi-Agent systems. behavioral responses to reinforcing signals, communications which transmit the internal states or social bonding between individuals, which could increase fitness in the context of evolution. Among some models of emotions that are described through the computational process exists different approaches to the proper concept of emotion. Each model results of the definition that is given to the emotional process. Since analysis of needs/satisfactions of the human being (24, 25), passing through the analysis of characteristics of the superior nervous system (26, 28), physiological changes (23, 31), neurobiological processes (27), appraisal mechanism and analysis of the psychology of individual
Year
Venue
Keywords
2008
Clinical Orthopaedics and Related Research
system performance,social interaction,nervous system,artificial intelligent,multi agent system,human behavior,computer model
Field
DocType
Volume
Social relation,Computer science,Multi-agent system,Computational model,Artificial intelligence,Modular design,Affect (psychology),Cognition,Perception,Machine learning,Scalability
Journal
abs/0809.4
Citations 
PageRank 
References 
1
0.39
5
Authors
3
Name
Order
Citations
PageRank
Luís Paulo Reis148283.34
Daria Barteneva251.05
Nuno Lau310.72