μ-SATPLAN: Multi-agent planning as satisfiability

Dimopoulos, Yannis; Hashmi, Muhammad Adnan; Moraïtis, Pavlos

doi:10.1016/j.knosys.2011.07.019

Cited by 20 publications

(16 citation statements)

References 15 publications

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“…This explains also why, as shown in the following, we are able to achieve much higher scalability than state-of-the-art multiagent plan synthesis algorithms, (e.g., Dimopoulos et al, 2012;Nissim et al, 2010;Torreno et al, 2012). The algorithms exploit "locality" in different ways in order to be able to plan for parts of a multiagent planning problem while temporarily ignoring others, for example, by considering noninteracting subplans in isolation from each other.…”

Section: Related Workmentioning

confidence: 84%

Ridesharing on Timetabled Transport Services: A Multiagent Planning Approach

Hrncir

Rovatsos

Jakob

2015

Journal of Intelligent Transportation Systems

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Ridesharing, that is, the problem of finding parts of routes that can be shared by several travelers with different points of departure and destinations, is a complex, multiagent decision-making problem. The problem has been widely studied but only for the case of ridesharing using freely moving vehicles not bound to fixed routes and/or schedules-ridesharing on timetabled public transport services has not been previously considered. In this article, we address this problem and propose a solution employing strategic multiagent planning that guarantees that for any shared journey plan found, each individual is better off taking the shared ride rather than traveling alone, thus providing a clear incentive to participate in it. We evaluate the proposed solution on real-world scenarios in terms of the algorithm's scalability and the ability to address the inherent trade-off between cost savings and the prolongation of journey duration. The results show that under a wide range of circumstances our algorithm finds attractive shared journey plans. In addition to serving as a basis for traveler-oriented ridesharing service, our system allows stakeholders to determine appropriate pricing policies to incentivize group travel and to predict the effects of potential service changes.

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Section: Related Workmentioning

confidence: 84%

Ridesharing on Timetabled Transport Services: A Multiagent Planning Approach

Hrncir

Rovatsos

Jakob

2015

Journal of Intelligent Transportation Systems

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show abstract

“…Brafman and Domshlak (2008) applied constraint satisfaction and factored planning to produce plans for multi-agent problems, which was extended to use distributed constraint satisfaction solvers (Nissim et al, 2010). Another satisfiability based planner, µ-SATPLAN extended SATPLAN to multi-agent planning for two distinct classes of problems: multi-agent coordinated actions and multi-agent assistance actions (Dimopoulos et al, 2012).…”

Section: Ii35 Multi-agentmentioning

confidence: 99%

Hybrid mission planning with coalition formation

Dukeman

Adams

2017

Auton Agent Multi-Agent Syst

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“…The authors in [15] propose an approach to coordinate the course of agents' actions operating in the same environment in two different settings: when agents by themselves are able to achieve their individual goals and when agents need other agents to reach their individual goals. The authors extend the classical SATPLAN planner to deal with the problem of multi-agent planning by handling negative (i.e., harmful) and positive interactions in order to finally discover consistent plans for multiple agents.…”

Section: Practical and Industrial Settingsmentioning

confidence: 99%