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.
|Number of pages||5|
|Publication status||Published - 1996|
|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||Proceedings of the 1996 IEEE International Conference on Neural Networks, ICNN. Part 1 (of 4)|
|City||Washington, DC, USA|
|Period||03.06.1996 → 06.06.1996|