TY - GEN
T1 - Automated verification of social laws for continuous time multi-robot systems
AU - Nir, Ronen
AU - Karpas, Erez
N1 - Publisher Copyright:
© 2019, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
PY - 2019/1/1
Y1 - 2019/1/1
N2 - Designing multi-agent systems, where several agents work in a shared environment, requires coordinating between the agents so they do not interfere with each other. One of the canonical approaches to coordinating agents is enacting a social law, which applies restrictions on agents' available actions. A good social law prevents the agents from interfering with each other, while still allowing all of them to achieve their goals. Recent work took the first step towards reasoning about social laws using automated planning and showed how to verify if a given social law is robust, that is, allows all agents to achieve their goals regardless of what the other agents do. This work relied on a classical planning formalism, which assumed actions are instantaneous and some external scheduler chooses which agent acts next. However, this work is not directly applicable to multi-robot systems, because in the real world actions take time and the agents can act concurrently. In this paper, we show how the robustness of a social law in a continuous time setting can be verified through compilation to temporal planning. We demonstrate our work both theoretically and on real robots.
AB - Designing multi-agent systems, where several agents work in a shared environment, requires coordinating between the agents so they do not interfere with each other. One of the canonical approaches to coordinating agents is enacting a social law, which applies restrictions on agents' available actions. A good social law prevents the agents from interfering with each other, while still allowing all of them to achieve their goals. Recent work took the first step towards reasoning about social laws using automated planning and showed how to verify if a given social law is robust, that is, allows all agents to achieve their goals regardless of what the other agents do. This work relied on a classical planning formalism, which assumed actions are instantaneous and some external scheduler chooses which agent acts next. However, this work is not directly applicable to multi-robot systems, because in the real world actions take time and the agents can act concurrently. In this paper, we show how the robustness of a social law in a continuous time setting can be verified through compilation to temporal planning. We demonstrate our work both theoretically and on real robots.
UR - https://www.scopus.com/pages/publications/85090802796
U2 - 10.1609/aaai.v33i01.33017683
DO - 10.1609/aaai.v33i01.33017683
M3 - Conference contribution
AN - SCOPUS:85090802796
T3 - 33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019
SP - 7683
EP - 7690
BT - 33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019
PB - AAAI press
T2 - 33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Annual Conference on Innovative Applications of Artificial Intelligence, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019
Y2 - 27 January 2019 through 1 February 2019
ER -