Reasoning for Autonomous Agents in Dynamic Domains

Stephan Opfer, Stefan Jakob, Kurt Geihs


In contrast to simple autonomous vacuum cleaners, multi-purpose robots that fetch a cup of coffee and clean up rooms require cognitive skills such as learning, planning, and reasoning. Especially reasoning in dynamic and human populated environments demands for novel approaches that can handle comprehensive and fluent knowledge bases. A promising approach is Answer Set Programming (ASP), offering multi-shot solving techniques and non-monotonic stable model semantics. Our objective is to equip multi-agent systems with ASP-based reasoning capabilities, enabling a team of robots to cope with dynamic environments. Therefore, we combined ALICA - A Language for Interactive Cooperative Agents - with the ASP solver Clingo and chose topological path planning as our evaluation scenario. We utilised the Region Connection Calculus as underlying formalism of our evaluation and investigated the scalability of our implementation. The results show that our approach handles dynamic environments and scales up to appropriately large problem sizes.


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Paper Citation

in Harvard Style

Opfer S., Jakob S. and Geihs K. (2017). Reasoning for Autonomous Agents in Dynamic Domains . In Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-220-2, pages 340-351. DOI: 10.5220/0006297603400351

in Bibtex Style

author={Stephan Opfer and Stefan Jakob and Kurt Geihs},
title={Reasoning for Autonomous Agents in Dynamic Domains},
booktitle={Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},

in EndNote Style

JO - Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Reasoning for Autonomous Agents in Dynamic Domains
SN - 978-989-758-220-2
AU - Opfer S.
AU - Jakob S.
AU - Geihs K.
PY - 2017
SP - 340
EP - 351
DO - 10.5220/0006297603400351