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 Click to edit Formation the outline in Cooperative text format Game Theory. Second Outline Level 2. Coalition Formation Third Outline in Level Argumentation. Fourth Outline Level 3. The Issues and Fifth Problems OutlineBetween Level these Two Approaches. Sixth Outline Level Seventh Outline Level 4. My Research. Eighth Outline Level Ninth Outline LevelClick to edit Master text styles Second level Third level Fourth level Fifth level 2 1. Coalition Formation in Cooperative Game Theory (CGT) 3 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. 4 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. 5 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: e.g. e.g.Example Example2: 1:Given Givenaacoalition coalitiongame gamewhere whereN N== {1,2}, v({1}) = v({2}) = 5 and v({1,2}) = 20 the proposed core outcome is <{1,2}, x(10,10) x(15,5) >> Yet core payoffs can sometimes be unfair [2] D. Gillies. Some theorems on n-person games. PhD thesis, Princeton University, 1953. 6 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 1/3core 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. 7 1. Coalition Formation in Argumentation 8 Dung's Initial Work Dung showed that Argumentation Frameworks were natural ways to represent n-person games, for example theorem 6 of [4]: The AF represents 3 possible payoff vectors of the coalition game: x(3,4,8) v({1}) = v({2}) = v({3}) = 3 v({1,3}) = 8 x(3,3,5) x(3,3,3) v({2,3}) = 12 or v(C) = 0 [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. 9 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. 10 2. The Issues of Joining the Two Approaches 11 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,...) 12 My Current Research Question 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? 13 3. The Proposed Method 14 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:... 15 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) or each 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 16 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. 17 Core example Move Coalition {1} {2} {3} {1,2} {1,3} {2,3} {1,2,3} Coalition value 4 3 2 14 18 5 7 1 [3] 2 [9/9] [2] 3 [3] [10/4] [11/7] FINISH Coalition Structure of move 3 is {{1,3}, {2}}, the payoff vector is x(11,3,7) and is core stable 18 Epsilon-Core Example Move e value Coalition {1} value 5 0 5 {3} 5 {1,2} 5 {1,3} 18 {2,3} 20 [5] {1,2,3} 22 10 [11/11] 6 1 value 6 {2} 1 6 6 19 17 [6] 21 [7/12] Coalition Structure of move 8 is {{1},{2,3}}, the payoff vector is 7 stable 7 7 18 2 value and is 3-core 16 20 x(8,9.5,9.5) 7 2 [7] 8 3 value 8 3 8 [8/8] 8 15 17 [8] 19 [9.5/9.5] 19 4 value FINISH 9 9 9 14 16 18 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. 20 Thanks For Listening 21 Questions?