Integrated control and coordinated behavior: a case for agent models
ECAI-94 Proceedings of the workshop on agent theories, architectures, and languages on Intelligent agents
Modeling reactive behaviour in vertically layered agent architectures
ECAI-94 Proceedings of the workshop on agent theories, architectures, and languages on Intelligent agents
Forward models for physiological motor control
Neural Networks - 1996 Special issue: four major hypotheses in neuroscience
The Brain-Like Sensorimotor Control System
Journal of Intelligent and Robotic Systems
A Cooperation Model for Autonomous Agents
ECAI '96 Proceedings of the Workshop on Intelligent Agents III, Agent Theories, Architectures, and Languages
Vision: A Computational Investigation into the Human Representation and Processing of Visual Information
Drawing attention to the dangerous
ICANN/ICONIP'03 Proceedings of the 2003 joint international conference on Artificial neural networks and neural information processing
Cognitive Systems Research
2006 Special Issue: Attention as a controller
Neural Networks
Towards a control theory of attention
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part II
Combining attention and value maps
ICANN'05 Proceedings of the 15th international conference on Artificial Neural Networks: biological Inspirations - Volume Part I
A review of cognitive processing in the brain
ICANN'05 Proceedings of the 15th international conference on Artificial Neural Networks: biological Inspirations - Volume Part I
A computational model for multiple goals
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part I
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A new approach based on attention control ideas is presented. We introduce the framework of Attentional Agents as the theoretical framework for constructing enhanced agents. We propose an approach where an agent processes multiple, possibly conflicting, goals in parallel and it uses a number of signals for obtaining information about its environment and own state. Additional requirements include a fast response in a changing environment and working with incomplete information. The proposed framework integrates in a seamless manner, sub-symbolic and symbolic processing, feedback control, conflict resolution, processing of multiple concurrent goals and action generation. We apply the general framework to the development of a robotic agent and we provide results from simple simulations where usage of multi-modal information and competing goals are present so as to illustrate the general ideas.