Toward computational models of emotion
Selected and updated papers from the proceedings of the 1982 European conference on Progress in artificial intelligence
The society of mind
Introduction to the theory of neural computation
Introduction to the theory of neural computation
Proceedings of the first international conference on simulation of adaptive behavior on From animals to animats
Automatic programming of behavior-based robots using reinforcement learning
Artificial Intelligence
What computers still can't do: a critique of artificial reason
What computers still can't do: a critique of artificial reason
Reinforcement learning for robots using neural networks
Reinforcement learning for robots using neural networks
Affective computing
Modeling motivations and emotions as a basis for intelligent behavior
AGENTS '97 Proceedings of the first international conference on Autonomous agents
Emotion-driven learning for animat control
Proceedings of the fifth international conference on simulation of adaptive behavior on From animals to animats 5
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
An Architecture for Action, Emotion, and Social Behavior
MAAMAW '92 Selected papers from the 4th European Workshop on on Modelling Autonomous Agents in a Multi-Agent World, Artificial Social Systems
Old tricks, new dogs: ethology and interactive creatures
Old tricks, new dogs: ethology and interactive creatures
Reinforcement learning: a survey
Journal of Artificial Intelligence Research
A model for hormonal modulation of learning
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Asynchronous learning by emotions and cognition
ICSAB Proceedings of the seventh international conference on simulation of adaptive behavior on From animals to animats
Learning behavior-selection by emotions and cognition in a multi-goal robot task
The Journal of Machine Learning Research
On Cognition as Dynamical Coupling: An Analysis of Behavioral Attractor Dynamics
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Learning of shared attention in sociable robotics
Journal of Algorithms
Behavioral flexibility: an emotion based approach
IWANN'07 Proceedings of the 9th international work conference on Artificial neural networks
An analysis of behavioral attractor dynamics
ECAL'07 Proceedings of the 9th European conference on Advances in artificial life
Mobile robot navigation modulated by artificial emotions
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Self-Organizing Sensorimotor Maps Plus Internal Motivations Yield Animal-Like Behavior
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Multi-policy optimization in self-organizing systems
SOAR'09 Proceedings of the First international conference on Self-organizing architectures
Emotion-based intrinsic motivation for reinforcement learning agents
ACII'11 Proceedings of the 4th international conference on Affective computing and intelligent interaction - Volume Part I
Modelling Shared Attention Through Relational Reinforcement Learning
Journal of Intelligent and Robotic Systems
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The adaptive value of emotions in nature indicates that they might also be useful in artificial creatures. Experiments were carried out to investigate this hypothesis in a simulated learning robot. For this purpose, a non-symbolic emotion model was developed that takes the form of a recurrent artificial neural network where emotions both depend on and influence the perception of the state of the world. This emotion model was integrated in a reinforcement-learning architecture with three different roles: influencing perception, providing reinforcement value, and determining when to reevaluate decisions. Experiments to test and compare this emotion-dependent architecture with a more conventional architecture were done in the context of a solitary learning robot performing a survival task. This research led to the conclusion that artificial emotions are a useful construct to have in the domain of behavior-based autonomous agents with multiple goals and faced with an unstructured environment, because they provide a unifying way to tackle different issues of control, analogous to natural systems' emotions.