Towards a general theory of action and time
Artificial Intelligence
Perceptual organization and the representation of natural form
Artificial Intelligence
Discrete-time signal processing
Discrete-time signal processing
Local feedback multilayered networks
Neural Computation
Visual surveillance in a dynamic and uncertain world
Artificial Intelligence - Special volume on computer vision
Fast planning through planning graph analysis
Artificial Intelligence
A cognitive architecture for artificial vision
Artificial Intelligence
Reasoning in description logics
Principles of knowledge representation
Remote Agent: to boldly go where no AI system has gone before
Artificial Intelligence - Special issue: artificial intelligence 40 years later
Artificial intelligence and mobile robots: case studies of successful robot systems
Artificial intelligence and mobile robots: case studies of successful robot systems
Extending Graphplan to handle uncertainty and sensing actions
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
A temporal description logic for reasoning about actions and plans
Journal of Artificial Intelligence Research
Robotics and Autonomous Systems
Data mining coupled conceptual spaces for intelligent agents in data-rich environments
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part IV
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An autonomous robot involved in missions should be able to generate, update and process its own actions. It is not plausible that the meaning of the actionsus ed by the robot isgiv en form the outside of the system itself. Rather, this meaning should be anchored to the world through the perceptual abilitiesof the robot. We present an approach to conceptual action representation based on a "conceptual" level that actsasan intermediate level between symbolsand data coming form sensors. Symbolic representations are interpreted by mapping them on the conceptual level through a mapping mechanism based on artificial neural networks.