Abstract
This paper presents the concept of an autonomous robotic agent combining reactive and machine learning-based algorithms. The focus is on the machine learning-based part that we implement by neural networks. A method for reducing the environment state space to a smaller conceptual world space is given. We then show how the concept of 'lifelong learning' can be implemented by neural networks in a robotic action planner.
Original language | English |
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Pages | 1682-1686 |
Number of pages | 5 |
Publication status | Published - 1996 |
Externally published | Yes |
Event | Proceedings of the 1996 IEEE International Conference on Neural Networks, ICNN. Part 1 (of 4) - Washington, DC, USA Duration: 3 Jun 1996 → 6 Jun 1996 |
Conference
Conference | Proceedings of the 1996 IEEE International Conference on Neural Networks, ICNN. Part 1 (of 4) |
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City | Washington, DC, USA |
Period | 03.06.1996 → 06.06.1996 |