International Workshop on
Optimisation in Multi-Agent Systems
In conjunction with AAMAS 2017
Sao Paolo, Brazil
May 9, 2017
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.
February 7, 2017February 20, 2017 - Extended Submission Deadline March 2, 2017March 13, 2017 - Extended Acceptance Notification March 9, 2017March 27, 2017 - Extended Camera-Ready Deadline
- May 9, 2017 - Workshop Date
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 minimising the exchange of private information.
- Solution quality bounds: problems requiring anytime and/or approximate algorithms with quality bounds.
- Robust optimisation: 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
OptMAS places particular emphasis on distributed constraint reasoning (DCR) approaches, which include the modeling, formulation and solution of DCR problems, including both Distributed Constraint Satisfaction and Optimization Problems. DCR problems arise when pieces of information about variables, constraints or both are relevant to independent but communicating agents. They provide a promising framework to deal with the increasingly diverse range of distributed real world problems emerging from the evolution of computation and communication technologies. Example DCR-specific technical issues include:
- unified frameworks for distributed constraint reasoning
- complete and incomplete algorithms for solving distributed constraint reasoning problems
- privacy issues in distributed constraint reasoning
- problem solving in systems with self-interested agents
- negotiation among self-interested agents
- distributed constraint propagation and consistency
- generation and formulation/modeling of distributed constraint reasoning
- applications of distributed constraint reasoning
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: http://www.springer.de/comp/lncs/authors.html.
All submissions are conducted via the OptMAS 2017 EasyChair website: http://www.easychair.org/conferences/?conf=optmas2017.
Submissions should include the name(s), affiliations, and email addresses of all authors. We welcome the submission of papers rejected from the AAMAS 2017 technical program. The deadline for receipt of submissions is February 7, 2017. 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.
The most "visionary paper" will be published by Springer in a book under the Lecture Notes in Artificial Intelligence (LNAI) - Hot Topics series. The book will be a compilation of the most visionary papers of the AAMAS-2017 Workshops, where one paper will be selected from each AAMAS-2017 workshop. Additionally, the "best paper" will be published by Springer in a book under the Communications in Computer and Information Science (CCIS) series. The book will be a compilation of the best papers of the AAMAS-2017 Workshops, where one paper will be selected from each AAMAS-2017 workshop. Authors of the selected most visionary paper and the best paper are expected to provide their latex files promptly upon request.
For questions about the submission process, contact the workshop co-chairs.
- Bo An, Nanyang Technological University
- Ana Bazzan, Universidade Federal do Rio Grande do Sul
- Filippo Bistaffa, University of Verona
- Ferdinando Fioretto, University of Michigan
- Tal Grinshpoun, Ariel University
- Cedric Herpson, University Pierre and Marie Curie
- Katsutoshi Hirayama, Kobe University
- Christopher Kiekintveld, University of Texas, El Paso
- Sven Koenig, University of Southern California
- Kate Larson, University of Waterloo
- Amnon Meisels, Ben-Gurion University
- Hala Mostafa, United Technologies Research Center
- Gauthier Picard, ENS Mines Saint-Etienne
- Juan Antonio Rodriguez Aguillar, IIIA-CSIC
- Onn Shehory, IBM Haifa Research Lab
- Marius Silaghi, Florida Institute of Technology
- Rinde van Lon, KU Leuven
- Mihaela Verman, University of Zurich
- Meritxell Vinyals, CEA-LIST
- Mohamed Wahbi, University College Cork
- Harel Yedidsion, Ben-Gurion University
- Logan Yliniemi, Oregon State University
- Makoto Yokoo, Kyushu University