The role of emotion in believable agents
Communications of the ACM
Emotion model for life-like agent and its evaluation
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Tears and fears: modeling emotions and emotional behaviors in synthetic agents
Proceedings of the fifth international conference on Autonomous agents
Metalearning and neuromodulation
Neural Networks - Computational models of neuromodulation
FLAME—Fuzzy Logic Adaptive Model of Emotions
Autonomous Agents and Multi-Agent Systems
Is it an Agent, or Just a Program?: A Taxonomy for Autonomous Agents
ECAI '96 Proceedings of the Workshop on Intelligent Agents III, Agent Theories, Architectures, and Languages
Agents and the algebra of emotion
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
From brows to trust: evaluating embodied conversational agents
From brows to trust: evaluating embodied conversational agents
Useful roles of emotions in artificial agents: a case study from artificial life
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Emotional agents in a social strategic game
KES'11 Proceedings of the 15th international conference on Knowledge-based and intelligent information and engineering systems - Volume Part I
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This paper proposes modeling of artificial emotions through agents based on symbolic approach. The symbolic approach utilizes symbolic emotional rule-based systems (rule base that generated emotions) with continuous interactions with environment and an internal ''thinking'' machinery that comes as a result of series of inferences, evaluation, evolution processes, adaptation, learning, and emotions. We build two models for agent based systems; one is supported with artificial emotions and the other one without emotions. We use both in solving a bench mark problem; ''The Orphanage Care Problem''. The two systems are simulated and results are compared. Our study shows that systems with proper model of emotions can perform in many cases better than systems without emotions. We try to shed the light here on how artificial emotions can be modeled in a simple rule-based agent systems and if emotions as they exist in ''real intelligence'' can be helpful for ''artificial intelligence''. Agent architectures are presented as a generic blueprint on which the design of agents can be based. Our focus is on the functional design, including flow of information and control. With this information provided, the generic blueprints of architectures should not be difficult to implement agents, thus putting these theoretical models into practice. We build the agents using this architecture, and many experiments and analysis are shown.