Constructing a unifying theory of dynamic programming DCOP algorithms via the generalized distributive law

Autonomous Agents and Multi-Agent Systems

Volumn 22, Issue 3, 2011, Pages 439-464

  Vinyals, Meritxell ^a   Rodriguez Aguilar, Juan A ^a   Cerquides, Jesús ^b  

^a ARTIFICIAL INTELLIGENCE RESEARCH INSTITUTE IIIA CSIC   (Spain)

^b UNIVERSITY OF BARCELONA   (Spain)

Author keywords

DCOP; DCPOP; DPOP; GDL; Generalized distributive law

Indexed keywords

DCOP; DCPOP; DPOP; GDL; GENERALIZED DISTRIBUTIVE LAWS;

ALGORITHMS; MESSAGE PASSING;

DYNAMIC PROGRAMMING;

EID: 79952901126     PISSN: 13872532     EISSN: 15737454     Source Type: Journal    
DOI: 10.1007/s10458-010-9132-7     Document Type: Article

References (23)

1. Aji S. M., McEliece R. J. (2000) The generalized distributive law. IEEE Transactions on Information Theory 46(2): 325-343.
2. Amir, E. (2001). Efficient approximation for triangulation of minimum treewidth. In: UAI, pp. 7-15.
3. Atlas, J., & Decker, K. (2007). A complete distributed constraint optimization method for non-traditional pseudotree arrangements. In: AAMAS, pp. 741-784.
4. Barbosa V. (1996) An introduction to distributed algorithms. The MIT Press, Cambridge.
5. Cano, A., & Moral, S. (1994). Heuristic algorithms for the triangulation of graphs. In: IPMU, pp. 98-107.
6. Dechter R. (2003) Constraint processing. Morgan Kaufmann, San Francisco.
7. Flores, M. J., Gámez, J. A., & Olesen, K. G. (2003). Incremental compilation of bayesian networks. In: UAI, pp. 233-240.
8. Jensen, F. V., & Jensen, F. (1994). Optimal junction trees. In: UAI, pp. 360-366.
9. Junges, R., & Bazzan, A. L. C. (2008). Evaluating the performance of DCOP algorithms in a real world, dynamic problem. In: AAMAS (Vol. 2, pp. 599-606).
10. Maheswaran, R. T., Tambe, M., Bowring, E., Pearce, J. P., & Varakantham, P. (2004). Taking DCOP to the real world: Efficient complete solutions for distributed multi-event scheduling. In: AAMAS, pp. 310-317.
11. Mailler, R., & Lesser, V. R. (2004). Solving distributed constraint optimization problems using cooperative mediation. In: AAMAS, pp. 438-445.
12. Modi P. J., Shen W. M., Tambe M., Yokoo M. (2005) Adopt: Asynchronous distributed constraint optimization with quality guarantees. Artif Intell 161(1-2): 149-180.
13. Pearl J. (1988) Probabilistic reasoning in intelligent systems. Morgan Kaufmann Publishers Inc, San Francisco, CA.
14. Petcu, A. (2007). A class of algorithms for distributed constraint optimization. PhD thesis, EPFL, Lausanne.
15. Petcu, A., & Faltings, B. (2005). A scalable method for multiagent constraint optimization. In: IJCAI, pp. 266-271.
16. Santoro, N. (2006). Design and analysis of distributed algorithms. (Wiley series on parallel and distributed computing) Chicheste: Wiley-Interscience.
17. Shafer G., Shenoy P. P. (1990) Probability propagation. Ann Math Artif Intell 2: 327-351.
18. Vinyals, M., Rodriguez-Aguilar, J., & Cerquides, J. (2008). Proving the equivalence of Action-GDL and DPOP. http://www. iiia. csic. es/files/pdfs/TRR200804. pdf.
19. Vinyals, M., Rodriguez-Aguilar, J. A., & Cerquides, J. (2009). Generalizing DPOP: Action-GDL, a new complete algorithm for DCOPs. In: OPTMAS second international workshop on optimization in agent systems.
20. Viterbi A. (1967) Error bounds for convolutional codes and an asymptotically optimum decoding algorithm. IEEE Transactions on Information Theory 13(2): 260-269.
21. Yeoh, W., Felner, A., & Koenig, S. (2009). Idb-adopt: A depth-first search dcop algorithm. In: CSCLP, Lecture notes in computer science 5655, 2009, pp 132-146.
22. Yin, Z. (2008). USC dcop repository. http://teamcore. usc. edu/dcop.
23. Zhang W., Wang G., Xing Z., Wittenburg L. (2005) Distributed stochastic search and distributed breakout: Properties, comparison and applications to constraint optimization problems in sensor networks. Artif Intell 161(1-2): 55-87.