The role of emotion in believable agents
Communications of the ACM
Affective computing
When robots weep: emotional memories and decision-making
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Emotion and computational neuroscience
The handbook of brain theory and neural networks
Using motives and artificial emotions for long-term activity of an autonomous robot
Proceedings of the fifth international conference on Autonomous agents
Designing Sociable Robots
CA '99 Proceedings of the Computer Animation
An immunological approach to dynamic behavior control for autonomous mobile robots
IROS '95 Proceedings of the International Conference on Intelligent Robots and Systems-Volume 1 - Volume 1
Behavior arbitration for autonomous mobile robots using emotion mechanisms
IROS '95 Proceedings of the International Conference on Intelligent Robots and Systems-Volume 3 - Volume 3
Architecture for an Artificial Immune System
Evolutionary Computation
Artificial homeostatic system: a novel approach
ECAL'05 Proceedings of the 8th European conference on Advances in Artificial Life
An architecture for affective management of systems of adaptive systems
MACE'10 Proceedings of the 5th IEEE international conference on Modelling autonomic communication environments
Emotions in autonomous agents: comparative analysis of mechanisms and functions
Autonomous Agents and Multi-Agent Systems
Ultrastable neuroendocrine robot controller
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Society of Mind cognitive agent architecture applied to drivers adapting in a traffic context
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
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This article investigates the effects of emotional intervention on artificial immune networks used for navigation of autonomous agents (simulated autonomous mobile robots). It is known from psychoneuroimmunology that stress influences the immune system response. From the various models of emotions related to stress available in literature, the computational model of the amygdala reported by Mochida, Ishiguro, Aoki, and Uchikawa (1995) is used in this article. The emotional intervention is implemented as a frustration signal coming from an artificial amygdala that influences the dynamics of antibody selection. A series of experiments with an autonomous agent implementing a collision-free goal-following behavior is presented in five simulated environments with different levels of difficulty. Two types of immune network based action selection mechanism are examined: (a) independently acting and (b) emotionally influenced. They are compared with each other in MATLAB simulations; their performance is estimated on the basis of time steps and their success in collision-free goal attainment. The artificial emotion mechanism modifies the immune response to overcome some difficult situations and to improve the performance of the behavior arbitration as a whole.