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Using Dialogue Games to Form Coalitions with Self-Interested Agents

Using Dialogue Games to Form Coalitions with Self-Interested Agents. Luke Riley Department of Computer Science University of Liverpool L.J.Riley@Liverpool.ac.uk. Supervisors: Katie Atkinson & Terry Payne. 1. Coalition Formation in Cooperative Game Theory.

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Using Dialogue Games to Form Coalitions with Self-Interested Agents

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  1. Using Dialogue Games to Form Coalitions with Self-Interested Agents Luke Riley Department of Computer Science University of Liverpool L.J.Riley@Liverpool.ac.uk Supervisors: Katie Atkinson & Terry Payne

  2. 1. Coalition Formation in Cooperative Game Theory. 2. Coalition Formation in Argumentation. 3. The Issues and Problems Between these Two Approaches. 4. My Research.

  3. 1. Coalition Formation in Cooperative Game Theory (CGT)

  4. Background • N-person cooperative games (coalition games) were proposed in 1944 by von Neumann & Morgenstern [1]: Where... Agent set: Characteristic Function: [1] J. von Neumann and O. Morgenstern. The Theory of Games and Economic Behavior. Princeton University Press, 1944.

  5. Solving a Coalition Game • In its most traditional style the CGT outcome of a coalition game is: Where... CS = a set of coalitions (the coalition structure) x = a vector of each individual agent's payoff in the game.

  6. Finding a Stable Outcome – The Core • A Coalition Structure is core-stable if no subset of agents can benefit from defecting to another coalition. • The core [2] is the set where: • Yet core payoffs can sometimes be unfair e.g. Example 1: Given a coalition game where N = {1,2}, v({1}) = v({2}) = 5 and v({1,2}) = 20 the proposed core outcome is <{1,2}, x(10,10) > e.g. Example 2: Given a coalition game where N = {1,2}, v({1}) = v({2}) = 5 and v({1,2}) = 20 the proposed core outcome is <{1,2}, x(15,5) > [2] D. Gillies. Some theorems on n-person games. PhD thesis, Princeton University, 1953.

  7. Epsilon-Core • Also the core can sometimes be empty e.g. Example 3: Given a coalition game where N = {1,2,3}, forall subsets C if |C| = 2 then v(C) = 1 else v(C) = 0 • Solution [3] → • The epsilon value can be seen as the cost of deviating. e.g. Example 4: Given the coalition game of example 3, the payoff vector x(1/3,1/3,1/3) is 1/3-core stable. [3] Shapley, Lloyd S. and Shubik, M. Quasi-cores in a monetary economy with non-convex preferences , Econometrica (The Econometric Society) 34(4): 805–827, 1966.

  8. 1. Coalition Formation in Argumentation

  9. Dung's Initial Work • Dung showed that Argumentation Frameworks were natural ways to represent n-person games, for example theorem 6 of [4]: x(3,4,8) The AF represents 3 possible payoff vectors of the coalition game: v({1}) = v({2}) = v({3}) = 3 v({1,3}) = 8 v({2,3}) = 12 or v(C) = 0 x(3,3,5) x(3,3,3) [4] P. M. Dung. On the acceptability of arguments and its fundamental role in nonmonotonic reasoning, logic programming and n-person games. Artificial Intelligence, 77:321–357, 1995.

  10. Amgoud's Further Research • Amgoud in [5] extended this research, where she highlighted: • How to always find a solution to a coalition game • Outlines how agents can collaboratively build AFs for coalition games • How a dialogue game can be used to check if a certain coalition was in the best coalition structure [5] L. Amgoud. An argumentation-based model for reasoning about coalition structures. In ArgMAS, pages 217-228, 2005.

  11. 2. The Issues of Joining the Two Approaches

  12. Various Issues • CGT: Lacks flexible communication protocols to form stable coalitions. • CGT: Generally does not take into account the computation and communication costs of finding stable coalition structures from a MAS perspective. • Arg: There is little research showing how payoff vectors are found and justified by MAS. • Arg: No research on how to stabilise coalitions games, using the epsilon-core • Arg: Only some limited direct mapping between the argumentation models and the CGT coalition game types (e.g. static, dynamic, skill games,...)

  13. How can self-interested agents make use of argumentation within their communication to enable them to form a stable optimal coalition structure with an approximately fair payoff distribution? My Current Research Question

  14. 3. The Proposed Method

  15. Dialogue Games & Argumentation Schemes • Dialogue Games can be used to build argumentation frameworks in real time, where agents can assert and retract arguments. • Argumentation schemes are patterns of reasoning that when instantiated provide presumptive justification for the particular conclusion of the scheme • e.g:...

  16. Approximately fair payoffs • AFs can easily represent the core • ...But the core can be unfair • Solution – restrict the payoffs allowed: • agents have to propose an equal split of v(C) oreach agent should be given at least the same value it can get from a coalition of agents willing to defect • Agents can object to a proposed payoff by finding a better one for itself. • Once a core payoff is found, the dialogue stops

  17. Dialogue Games & Argumentation Schemes • I have devised a dialogue game [6] to find an optimal coalition structure with a restricted core payoff • Moves: e.g: [6] L. Riley, K. Atkinson, and T. Payne. Coalition structure generation for self interested agents in a dialogue game. Technical Report ULCS-12-004, University of Liverpool, 2012.

  18. Core example Coalition Structure of move 3 is {{1,3}, {2}}, the payoff vector is x(11,3,7) and is core stable

  19. Epsilon-Core Example Coalition Structure of move 8 is {{1},{2,3}}, the payoff vector is x(8,9.5,9.5) and is 3-core stable

  20. Potential Future • Modify argumentation scheme and attack relations so that other coalition games can be modeled (e.g stochastic, dynamic, skill games,...). • Optimise process: Combine mechanism design approach of [7] with efficient distribution methods of [8]. [7] Tuomas Sandholm, Kate Larson, Martin Andersson, Onn Shehory and Fernando Tohmé, Coalition structure generation with worst case guarantees, Artificial Intelligence, Volume 111, Issues 1–2, July 1999, Pages 209-238. [8] T. Rahwan. Algorithms for Coalition Formation in Multi-Agent Systems. PhD thesis, University of Southampton, 2007.

  21. Thanks For Listening Questions?

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