caa a22 4500 605514852 CHVBK 20210128100706.0 cr unu---uuuuu 210128e20150901xx s 000 0 eng 10.1007/s10458-014-9274-0 doi (NATIONALLICENCE)springer-10.1007/s10458-014-9274-0 Risk management for self-adapting self-organizing emergent multi-agent systems performing dynamic task fulfillment [Elektronische Daten] [Jonathan Hudson, Jörg Denzinger] The goal of self-adapting self-organizing emergent multi-agent systems applied to problems with dynamically appearing tasks is to reduce operation and design costs. This is accomplished through the design of autonomous agents, which interact to produce behaviors required for flexible and scalable operation. However, when combined with agent autonomy, emergent behaviors are unpredictable resulting in a lack of trust for applications desiring efficiency such as logistics. An additional consultation agent, known as an efficiency improvement advisor (EIA), has been shown to increase efficiency through autonomy preserving advice provided as exception rule adaptations to agents. The problem addressed in this paper is that, in order for EIA-adapted systems to be deployed, the stakeholders must be assured that the risks of both autonomous and adapted behavior are properly assessed and managed. This paper presents a complete framework for a risk-aware EIA (RA-EIA) which uses reflection in order to manage the risks associated with autonomous agents and prospective adaptations. Monte Carlo simulation is used to reduce the frequency of emergent misbehavior appearing during regular operation. Meanwhile, an exploratory testing method, termed evolutionary learning of event sequences, is used to deal with the possibility of severe emergent misbehavior as the result of an malicious adversary or a series of unfortunate events. The experimental evaluations and accompanying descriptive example, for the application area of logistics via pickup and delivery problems, demonstrate that the risk-aware adaptations provided from consultation with the RA-EIA agent allow the client system to be trusted for long-term independent and reliable operational efficiency. The Author(s), 2014 Risk assessment nationallicence Risk management nationallicence Evolutionary testing nationallicence Emergence nationallicence Reflection nationallicence Efficiency nationallicence Multi-agent systems nationallicence Hudson Jonathan Department of Computer Science, University of Calgary, Calgary, Canada aut Denzinger Jörg Department of Computer Science, University of Calgary, Calgary, Canada aut Autonomous Agents and Multi-Agent Systems Springer US; http://www.springer-ny.com 29/5(2015-09-01), 973-1022 1387-2532 29:5<973 2015 29 10458 https://doi.org/10.1007/s10458-014-9274-0 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s10458-014-9274-0 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Hudson Jonathan Department of Computer Science, University of Calgary, Calgary, Canada aut NATIONALLICENCE 700 1- Denzinger Jörg Department of Computer Science, University of Calgary, Calgary, Canada aut NATIONALLICENCE 773 0- Autonomous Agents and Multi-Agent Systems Springer US; http://www.springer-ny.com 29/5(2015-09-01), 973-1022 1387-2532 29:5<973 2015 29 10458