Balancing local resources and global goals in multiply-constrained DCOP

Distributed constraint optimization (DCOP) is a useful framework for cooperative multiagent coordination. DCOP focuses on optimizing a single team objective. However, in many domains, agents must satisfy constraints on resources consumed locally while optimizing the team goal. Yet, these resource constraints may need to be kept private. Designing DCOP algorithms for these domains requires managing complex trade-offs in completeness, scalability, privacy and efficiency. This article defines the multiply-constrained DCOP (MC-DCOP) framework and provides complete (globally optimal) and incomplete (locally optimal) algorithms for solving MC-DCOP problems. Complete algorithms find the best allocation of scarce resources while optimizing the team objective, while incomplete algorithms are more scalable. The algorithms use four main techniques: (i) transforming constraints to maintain privacy; (ii) dynamically setting upper bounds on resource consumption; (iii) identifying the extent to which the local graph structure allows agents to compute exact bounds; and (iv) using a virtual assignment to flag problems rendered unsatisfiable by resource constraints. Proofs of correctness are presented for all algorithms. Experimental results illustrate the strengths and weaknesses of both the complete and incomplete algorithms.

[1]  Milind Tambe,et al.  Solution sets for DCOPs and graphical games , 2006, AAMAS '06.

[2]  Amnon Meisels,et al.  CompAPO: A Complete Version of the APO Algorithm , 2007 .

[3]  Boi Faltings,et al.  MB-DPOP: A New Memory-Bounded Algorithm for Distributed Optimization , 2007, IJCAI.

[4]  John Davin,et al.  Hierarchical variable ordering for distributed constraint optimization , 2006, AAMAS '06.

[5]  F. Y. Edgeworth Mathematical Psychics: An Essay on the Application of Mathematics to the Moral Sciences , 2007 .

[6]  Milind Tambe,et al.  Experimental analysis of privacy loss in DCOP algorithms , 2006, AAMAS '06.

[7]  Pankaj Jalote,et al.  Assigning tasks in a 24-hour software development model , 2004, 11th Asia-Pacific Software Engineering Conference.

[8]  Weixiong Zhang,et al.  An analysis and application of distributed constraint satisfaction and optimization algorithms in sensor networks , 2003, AAMAS '03.

[9]  Milind Tambe,et al.  Asynchronous algorithms for approximate distributed constraint optimization with quality bounds , 2010, AAMAS.

[10]  Makoto Yokoo,et al.  Distributed Constraint Satisfaction: Foundations of Cooperation in Multi-agent Systems , 2000 .

[11]  Marius-Calin Silaghi,et al.  Distributed constraint satisfaction and optimization with privacy enforcement , 2004, Proceedings. IEEE/WIC/ACM International Conference on Intelligent Agent Technology, 2004. (IAT 2004)..

[12]  Thomas Hanne,et al.  A multiobjective evolutionary algorithm for scheduling and inspection planning in software development projects , 2005, Eur. J. Oper. Res..

[13]  Katia P. Sycara,et al.  No-commitment branch and bound search for distributed constraint optimization , 2006, AAMAS '06.

[14]  Makoto Yokoo,et al.  Multiply-constrained distributed constraint optimization , 2006, AAMAS '06.

[15]  John Davin,et al.  Impact of problem centralization in distributed constraint optimization algorithms , 2005, AAMAS '05.

[16]  Sven Koenig,et al.  Caching schemes for DCOP search algorithms , 2009, AAMAS.

[17]  Edmund H. Durfee,et al.  A distributed framework for solving the Multiagent Plan Coordination Problem , 2005, AAMAS '05.

[18]  Nikos A. Vlassis,et al.  Anytime algorithms for multiagent decision making using coordination graphs , 2004, 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583).

[19]  X. Zhang,et al.  Solving Negotiation Chains in Semi-Cooperative Multi-Agent Systems , 2005 .

[20]  Toby Walsh,et al.  Encodings of Non-Binary Constraint Satisfaction Problems , 1999, AAAI/IAAI.

[21]  John Davin,et al.  Hierarchical Variable Ordering for Multiagent Agreement Problems , 2006 .

[22]  Manish Jain,et al.  On k-optimal distributed constraint optimization algorithms: new bounds and algorithms , 2008, AAMAS.

[23]  M. Yokoo,et al.  Distributed Breakout Algorithm for Solving Distributed Constraint Satisfaction Problems , 1996 .

[24]  Khaled Ghédira,et al.  Multicriteria Optimization in CSPs : Foundations and Distributed Solving Approach , 2004, AIMSA.

[25]  Victor R. Lesser,et al.  Solving distributed constraint optimization problems using cooperative mediation , 2004, Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, 2004. AAMAS 2004..

[26]  Federico Pecora,et al.  Reasoning about and dynamically posting n-ary constraints in ADOPT , 2006 .

[27]  Alok Aggarwal,et al.  Cooperative Multiobjective Decision Support for the Paper Industry , 1999, Interfaces.

[28]  Thomas Hanne,et al.  A Multi-Objective Evolutionary Algorithm for Scheduling and Inspection Planning in Software Development Projects , 2003 .

[29]  Nikolaos F. Matsatsinis,et al.  A Multi-criteria Protocol for Multi-agent Negotiations , 2004, SETN.

[30]  Makoto Yokoo,et al.  Resource constrained distributed constraint optimization using resource constraint free pseudo-tree , 2008, AAMAS.

[31]  Milind Tambe,et al.  Quality Guarantees on k-Optimal Solutions for Distributed Constraint Optimization Problems , 2007, IJCAI.

[32]  Makoto Yokoo,et al.  The Distributed Constraint Satisfaction Problem: Formalization and Algorithms , 1998, IEEE Trans. Knowl. Data Eng..

[33]  Stephen Fitzpatrick,et al.  Distributed Coordination through Anarchic Optimization , 2003 .

[34]  Jörg Denzinger,et al.  A General Framework for Multi-agent Search with Individual and Global Goals: Stakeholder Search , 2006, Int. Trans. Syst. Sci. Appl..

[35]  Amnon Meisels,et al.  Using additional information in DisCSPs search , 2004 .

[36]  Makoto Yokoo,et al.  Secure distributed constraint satisfaction: reaching agreement without revealing private information , 2002, Artif. Intell..

[37]  Marco Gavanelli,et al.  An Algorithm for Multi-Criteria Optimization in CSPs , 2002, ECAI.

[38]  Milind Tambe,et al.  Preprocessing techniques for accelerating the DCOP algorithm ADOPT , 2005, AAMAS '05.

[39]  Milind Tambe,et al.  Valuations of Possible States (VPS): a quantitative framework for analysis of privacy loss among collaborative personal assistant agents , 2005, AAMAS '05.

[40]  Amal El Fallah Seghrouchni,et al.  An Aggregation-Disaggregation Approach for Automated Negotiation in Multi-Agent Systems , 2000 .

[41]  Milind Tambe,et al.  Distributed Algorithms for DCOP: A Graphical-Game-Based Approach , 2004, PDCS.

[42]  Amedeo Cesta,et al.  DCOP FOR SMART HOMES: A CASE STUDY , 2007, Comput. Intell..

[43]  Makoto Yokoo,et al.  Nogood based asynchronous distributed optimization (ADOPT ng) , 2006, AAMAS '06.

[44]  Boi Faltings,et al.  Optimizing Streaming Applications with Self-Interested Users using MDPOP , 2006 .

[45]  Milind Tambe,et al.  Taking DCOP to the real world: efficient complete solutions for distributed multi-event scheduling , 2004, Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, 2004. AAMAS 2004..

[46]  Michael D. Smith,et al.  Improving privacy in distributed constraint optimization , 2007 .

[47]  Makoto Yokoo,et al.  Adopt: asynchronous distributed constraint optimization with quality guarantees , 2005, Artif. Intell..

[48]  J. Alberto Espinosa,et al.  The impact of time separation on coordination in global software teams: a conceptual foundation , 2003, Softw. Process. Improv. Pract..

[49]  Michael P. Wellman,et al.  Distributed quiescence detection in multiagent negotiation , 2000, Proceedings Fourth International Conference on MultiAgent Systems.

[50]  相場亮 Distributed Constraint Satisfaction: Foundations of Cooperation in Multi - Agent Systems , 2001 .

[51]  Nicholas R. Jennings,et al.  Bounded approximate decentralised coordination via the max-sum algorithm , 2009, Artif. Intell..

[52]  Boi Faltings,et al.  A Scalable Method for Multiagent Constraint Optimization , 2005, IJCAI.

[53]  Milind Tambe,et al.  Distributed Sensor Networks: A Multiagent Perspective , 2003 .

[54]  Sven Koenig,et al.  BnB-ADOPT: an asynchronous branch-and-bound DCOP algorithm , 2008, AAMAS.