Robotic agent control combining reactive and learning capabilities

Witold Jacak, Stephan Dreiseitl

Research output: Contribution to conferencePaperpeer-review

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 languageEnglish
Pages1682-1686
Number of pages5
Publication statusPublished - 1996
Externally publishedYes
EventProceedings of the 1996 IEEE International Conference on Neural Networks, ICNN. Part 1 (of 4) - Washington, DC, USA
Duration: 3 Jun 19966 Jun 1996

Conference

ConferenceProceedings of the 1996 IEEE International Conference on Neural Networks, ICNN. Part 1 (of 4)
CityWashington, DC, USA
Period03.06.199606.06.1996

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