Requirements Planning with Event Calculus for Self-adaptive Multi-agent System

Wei Liu, Feng Yao, Ming Li

Abstract

Self-adaptation of Multi-agent cooperative systems requires dynamic decision making and planning at runtime. Modeling the contextual and executable requirements of such systems as planning actions and states, this paper proposes a requirements-driven planning approach to self-adaptation. The planning model includes the states of the system context and the actions describing the behaviors of its multiple agents; the interactions between these agents and their environment are computed through an expansion of the requirements-driven planning graph, which is then used to verify whether the agents can collaborate in order to reach the desired goal states from their current states. In addition, the requirements are represented for Event Calculus to facilitate monitoring and reasoning about the actions of agents, achieving requirements driven planning at runtime.

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Paper Citation


in Harvard Style

Liu W., Yao F. and Li M. (2016). Requirements Planning with Event Calculus for Self-adaptive Multi-agent System . In Proceedings of the 8th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-758-172-4, pages 110-117. DOI: 10.5220/0005660001100117


in Bibtex Style

@conference{icaart16,
author={Wei Liu and Feng Yao and Ming Li},
title={Requirements Planning with Event Calculus for Self-adaptive Multi-agent System},
booktitle={Proceedings of the 8th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2016},
pages={110-117},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005660001100117},
isbn={978-989-758-172-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 8th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - Requirements Planning with Event Calculus for Self-adaptive Multi-agent System
SN - 978-989-758-172-4
AU - Liu W.
AU - Yao F.
AU - Li M.
PY - 2016
SP - 110
EP - 117
DO - 10.5220/0005660001100117