This OptMAS workshop invites works from different strands of the multi-agent systems community that pertain to the design of algorithms, models, and techniques to deal with multi-agent optimization problems. We will also place a particular emphasis on DCR approaches, which include the modeling, formulation and solution of DCR problems, including both Distributed Constraint Satisfaction and Optimization Problems.


The number of novel applications of multi-agent systems has followed an exponential trend over the last few years, ranging from online auction design, through multi-sensor networks, to scheduling of tasks in multi-actor systems. Multi-agent systems designed for all these applications generally involve some form of very hard optimization problems that are substantially different from problems traditionally dealt with in other areas (e.g. industrial processes or scheduling applications). More specifically, the technical issues that multi-agent algorithm designers have to deal with include:
  • Open systems: algorithms to compute solutions to mechanisms that deal with different stakeholders, who may be self-interested or may have different computation or communication capabilities from their peers.
  • Distributed systems: algorithms that are across different system components, such as those that deal with agents that are tied to physical devices. This involves considerations of computation and communication constraints, and the possibility of failures of the components and/or communication links.
  • Privacy concerns: solving optimization problems while minimizing the exchange of private information.
  • Solution quality bounds: problems requiring anytime and/or approximate algorithms with quality bounds.
  • Robust optimization: techniques to deal with optimizations that are repeated with only slight changes in the input data and/or with unreliable input data, which require solutions that are robust to these differences.
  • Highly parallel architectures: e.g., multi-core, GPGPU, which deal with large-scale problems with massive data and task parallelism.
In particular, workshop organizers are seeking papers on the following (but not limited to) topics:
  • Distributed constraint optimization/satisfaction
  • Winner determination algorithms in auctions
  • Coalition formation algorithms
  • Algorithms to compute Nash and other equilibria in games
  • Optimization under uncertainty
  • Optimization with incomplete or dynamic input data
  • Algorithms for real-time applications
  • GPU for general purpose computations (GPGPU)
  • Multi-core and many-core computing
  • Cloud, distributed and grid computing

Submission Information

Participants should submit a paper (maximum 15 pages), describing their work on one or more of the topics relevant to the workshop. Alternatively, participants may submit a shorter paper (maximum 5 pages) presenting a research statement or perspective on topics relevant to the workshop. Accepted papers will be presented during the workshop and will be published in the workshop proceedings.

Authors are requested to prepare their papers by following the LNCS Springer instructions found at:

All submissions are conducted via the OptMAS 2018 EasyChair website:

Submissions should include the name(s), affiliations, and email addresses of all authors. We welcome the submission of papers rejected from the AAMAS/IJCAI/ECAI/ICML 2018 technical program. The deadline for receipt of submissions is April 27, 2018. Papers received after this date may not be reviewed.
Submissions will be refereed on the basis of technical quality, novelty, significance, and clarity. Each submission will be thoroughly reviewed by at least two program committee members.

For questions about the submission process, contact the workshop co-chairs.

Important Dates

  • April 23, 2018 - Submission Deadline -- Extended: 27 April 2018
  • May 29, 2018 - Acceptance Notification
  • June 16, 2018 - Camera-Ready Deadline
  • July 14, 2018 - Workshop Date (Full day)

Technical Program

Location: K13

Accepted Papers

  • Jesus Cerquides, Rémi Emonet, Gauthier Picard and Juan Antonio Rodriguez Aguilar.
    Improving Max-Sum through Decimation to Solve Loopy Distributed Constraint Optimization Problems
  • Liel Cohen and Roie Zivan.
    Balancing Asymmetry in Max-sum using Split Constraint Factor Graphs
  • Moran Feldman and Rica Gonen.
    Removal and Threshold Pricing: Truthful Two-sided Markets with Multi-dimensional Participants
  • Ferdinando Fioretto, Hong Xu, Sven Koenig and T. K. Satish Kumar.
    Solving Multiagent Constraint Optimization Problems on the Constraint Composite Graph
  • Pierre Rust, Gauthier Picard and Fano Ramparany.
    Self-Organized and Resilient Distribution of Decisions over Dynamic Multi-Agent Systems
  • Coen van Leeuwen and Przemyslaw Pawelczak.
    Hybrid DCOP Solvers: Boosting Performance of Local Search Algorithms
  • Zheyuan Ryan Shi, Ziye Tang, Long Tran-Thanh, Rohit Singh and Fei Fang.
    Designing the Game to Play: Optimizing Payoff Structure in Security Games
  • Alvaro Perez-Diaz, Enrico Gerding and Frank McGroarty.
    Decentralised Coordination of Electric Vehicle Aggregators
  • Vinicius Renan de Carvalho and Jaime Sichman.
    Solving real-world multi-objective engineering optimization problems with an Election-Based Hyper-Heuristic
  • Yevgeniy Vorobeychik.
    Path Planning Games
  • Ricardo Faia, Tiago Pinto and Zita Vale.
    Multi-agent optimization of electricity markets participation portfolio with NPSO-LRS
  • Abdullah Al-Dujaili, Erik Hemberg and Unamay Oreilly.
    Approximating Nash Equilibria for Black-Box Games: A Bayesian Optimization Approach
  • Rica Gonen and Ozi Egri.
    Two-sided Markets: Mapping Social Welfare to Gain from Trade
  • Danny Hermelin, Michael Segal and Harel Yedidsion.
    Coordination of Mobile Agents for Wireless Sensor Network Maintenance
  • Anjon Basak, Marcus Gutierrez and Christopher Kiekintveld.
    Algorithms for Subgame Abstraction with Applications to Cyber Defense

Invited Speaker

Amnon Meisels

Ben Gurion University

Incentive-based Search by Selfish Agents

Abstract: Search for stable solutions in games is a hard problem that includes two families of constraints. The global stability constraint and multiple soft constraints that express preferences for socially preferred solutions. The talk will focus on distributed search by multi-agents, to find stable solutions (e.g., pure Nash equilibria - PNEs) of high efficiency. The multiple agents perform distributed search on an asymmetric distributed constraints optimization problem (ADCOP).
Three families of multi-agents games will be very briefly presented. Boolean games will be presented together with complete search algorithms that incorporate two kinds of incentives - taxation and side-payments. Next, the family of Public Goods Games (PGGs) will be presented and serve to discuss approximate (local) distributed search for a PNE that uses incentives. Since PGGs are shown to be potential games, the convergence of best-response is guaranteed. The use of incentives will enable best-response to converge to a PNE of higher social welfare.
Finally, for general games, a distributed local search algorithm that uses transfer of funds among selfish agents will be presented. The final outcome of the algorithm can be stabilized by transfer of funds among the agents, where the transfer function is contracted among the agents during search. The proposed algorithm - Iterative Nash Efficiency enhancement Algorithm (INEA) - guarantees improved efficiency for any initial outcome. It can be looked at as an extension to best response dynamics, that uses transfer functions to guarantee convergence and enforce stability in games. Unlike best-response, the proposed INEA converges to efficient and stable outcomes even in games that are not potential games.

Panel Discussion

Topic Distributed AI for the Internet of the Things
Members Bo An, Mattew Taylor, Gauthier Picard

Past Editions

Program Committee

  • Bo An - Nanyang Technological University
  • Juan Antonio Rodriguez Aguilar - IIIA-CSIC
  • Ana L. C. Bazzan - Universidade Federal do Rio Grande do Sul
  • Filippo Bistaffa - IIIA-CSIC
  • Tal Grinshpoun - Ariel University
  • Katsutoshi Hirayama - Kobe University
  • Tom Holvoet - KU Leuven
  • Christopher Kiekintveld - University of Texas at El Paso
  • Sven Koenig - University of Southern California
  • Kate Larson - University of Waterloo
  • Tiep Le - New Mexico State University
  • Amnon Meisels - Ben Gurion University of the Negev
  • Gauthier Picard - Laboratoire Hubert Curien MINES Saint-Etienne
  • Enrico Pontelli - New Mexico State University
  • Valentin Robu - Heriot-Watt University, Edinburgh
  • Marius Silaghi - FIT
  • Mohamed Wahbi - Insight, University College Cork
  • Harel Yedidsion - Ben-Gurion University Israel
  • William Yeoh - Washington University in St. Louis
  • Makoto Yokoo - Kyushu University


Workshop Co-Chairs:
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