The role of learning in autonomous robots
| Abstract | Applications of learning to autonomous agents (simulated or real) have often been restricted to learning a mapping from perceived state of the world to the next action to take. Often this is couched in terms of learning from no previous knowledge. This general case for real autonomous robots is very difficult. In any case, when building a real robot there is usually a lot of a priori knowledge (e.g., from the engineering that went into its design) which doesn’t need to be learned. We describe the behavior-based approach to autonomous robots, and then examine four classes of learning problems associated with such robots. | |||||||||
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Shaun Gallagher (2006). Where's the Action? Epiphenomenalism and the Problem of Free Will. In Susan Pockett, William P. Banks & Shaun Gallagher (eds.), Does Consciousness Cause Behavior? MIT Press.
Patrizia Marti (2010). Robot Companions: Towards a New Concept of Friendship? Interaction Studies 11 (2):220-226.
C. T. A. Schmidt & F. Kraemer (2006). Robots, Dennett and the Autonomous: A Terminological Investigation. Minds and Machines 16 (1):73-80.
Ludovic Marin & Olivier Oullier (2001). When Robots Fail: The Complex Processes of Learning and Development. Behavioral and Brain Sciences 24 (6):1067-1068.
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