Modeling motivations and emotions as a basis for intelligent behavior
AGENTS '97 Proceedings of the first international conference on Autonomous agents
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Metalearning and neuromodulation
Neural Networks - Computational models of neuromodulation
Neuromodulation and Plasticity in an autonomous robot
Neural Networks - Computational models of neuromodulation
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
A dynamic allocation method of basis functions in reinforcement learning
AI'04 Proceedings of the 17th Australian joint conference on Advances in Artificial Intelligence
IEEE Transactions on Neural Networks
Levels and Types of Action Selection: The Action Selection Soup
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Evolution of recollection and prediction in neural networks
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Simulation of how neuromodulation influences cooperative behavior
SAB'10 Proceedings of the 11th international conference on Simulation of adaptive behavior: from animals to animats
A review of long-term memory in natural and synthetic systems
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
The morphofunctional approach to emotion modelling in robotics
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Emotion as morphofunctionality
Artificial Life
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Neural Computation
Assembling old tricks for new tasks: A neural model of instructional learning and control
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Social contracts and human-computer interaction with simulated adapting agents
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Performance analysis on visual attention using spiking and oscillatory neural model
International Journal of Computational Vision and Robotics
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Biological organisms have the ability to respond quickly to an ever-changing world. Because this adaptability is so critical for survival, all vertebrates have sub-cortical structures, which comprise the neuromodulatory systems, to regulate fundamental behavior and drive decision making in response to environmental events. In the vertebrate, there are separate neuromodulators that respond to threats, reward anticipation, novelty, and attentional effort. However, each of these neuromodulatory systems has a similar effect, that is, to cause an organism to be decisive when environmental conditions call for such actions, and allow the organism to be more exploratory when there are no pressing events. In this article, it is proposed that principles of the neuromodulatory system could provide a framework for controlling artificial agents that may improve current artificial agent behavior. These agents would operate autonomously, effectively explore their environment, and be decisive when environmental conditions call for action.