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Easy and hard coalition resource game formation problems: a parameterized complexity analysis
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International Conference on Autonomous Agents archive
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1 table of contents
Budapest, Hungary
SESSION: Coalitions table of contents
Pages 433-440  
Year of Publication: 2009
ISBN:978-0-9817381-6-1
Authors
Tammar Shrot  Bar Ilan University, Ramat-Gan, Israel
Yonatan Aumann  Bar Ilan University, Ramat-Gan, Israel
Sarit Kraus  Bar Ilan University, Ramat-Gan, Israel
Sponsors
: The Foundation for Intelligent Physical Agents
Microsoft Research : Microsoft Research
: Wiley - Blackwell Ltd
: Whitestein Technologies
: European Office of Aerospace Research and Development, Air Force Office of Scientific Research, United States Air Force Research Laboratory
: Drexel University
Publisher
Bibliometrics
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ABSTRACT

Coalition formation is a key topic in multi--agent systems (mas). Coalitions enable agents to achieve goals that they may not have been able to achieve independently, and encourages resource sharing among agents with different goals.

A range of previous studies have found that problems in coalitional games tend to be computationally complex. However, such hardness results consider the entire input as one, ignoring any structural information on the instances. In the case of coalition formation problems, this bundles together several distinct elements of the input, e.g. the agent set, the goal set, the resources, etc. In this paper we reexamine the complexity of coalition formation problems in the coalition resources game model, as a function of their distinct input elements, using the theory of parameterized complexity. The analysis shows that not all parts of the input are created equal, and that many instances of the problem are actually tractable. We show that the problems are FPT in the number of goals, implying that if the number of goals is bounded then an efficient algorithm is available. Similarly, the problems are FPT in the combination of the number of agents and resources, again implying that if these parameters are bounded, then an efficient algorithm is available. On the other hand, the problems are para-NP hard in the number of resources, implying that even if we bound the number of resources the problems (probably) remain hard. Additionally, we show that most problems are W[1]-hard in the size of the coalition of interest, indicating that there is (probably) no algorithm polynomial in all but the coalition size. The exact definitions of the parameterized complexity notions FPT, Para-NP and W[1] are provided herein.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
A. H. Bond and L. Gasser, editors. Readings in Distributed Artificial Intelligence. Morgan Kaufmann Publishers: San Mateo, CA, 1988.
 
2
 
3
R. Downey. Parameterized complexity for the skeptic. In Proc. 18th IEEE Annual Conference on Computational Complexity, pages 147--169, 2003.
 
4
 
5
 
6
R. G. Downey and M. R. Fellows. Parameterized complexity after almost ten years: review and open questions. In Combinatorics, Computation and Logic, DMTCS'99 and CATS'99. Australian Computer Science Communications, Springer-Verlag, Singapore, vol. 21, pages 1--33, 1999.
 
7
 
8
 
9
 
10
 
11
 
12
O. Shehory and S. Kraus. Coalition formation among autonomous agents: Strategies and complexity. In C. Castelfranchi and J.-P. Müller, editors, From Reaction to Cognition --- Fifth European Workshop on Modelling Autonomous Agents in a Multi-Agent World, MAAMAW-93 (LNAI Volume 957), pages 56--72. Springer-Verlag: Berlin, Germany, 1995.
 
13
 
14
G. Weiß, editor. Multi-Agent Systems. The MIT Press: Cambridge, MA, 1999.
 
15
 
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Collaborative Colleagues:
Tammar Shrot: colleagues
Yonatan Aumann: colleagues
Sarit Kraus: colleagues