3C L Apport De La ThéOrie Des Jeux à L Intelligence Te Rritoriale Illustration From A Case M.Carrard

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3C L Apport De La ThéOrie Des Jeux à L Intelligence Te Rritoriale Illustration From A Case M.Carrard

  1. 1. Game Theory and Territorial Intelligence Illustration from a Case Study Michel Carrard National School of Engineering, Bourges 1 RESO-UMR 6590, Rennes 2 University
  2. 2. The objective of this contribution is to present the principles of a methodological work that has mobilized game theory to illuminate a town and country planning issue (Carrard, 2009): 2
  3. 3. PLAN 1 Context and Study Stakes 2 Methodology: Game Theory 3 The “Community Game” 4 Conclusion and Prospects 3
  4. 4. Context and Study Stakes: the transfer of Nantes Atlantique airport Aéroport NDDL 4 http://www.aeroport-grandouest.fr
  5. 5. Context and Study Stakes: the main components of NDDL airport 5 Dossier d’enquête préalable à la déclaration d’utilité publique, DGAC, 2006.
  6. 6. Context and Study Stakes: the impact of future NDDL airport Western and northern Britain: no impact Rennes: high impact Nantes-Rennes: high impact Secondary urban centers: high impact Zone of influence of NDDL airport: high NDDL airport: very high impact impact Nantes: very high impact Rural area: low impact 6 Ernst&Young, CG d’Ille et Vilaine, 2006
  7. 7. Context and Study Stakes: problems What status for future NDDL airport ? Two options were discussed during the Public Debate (2003): 1) NDDL : « the largest airport in the West ? » Resulting from competition between airports or 2) NDDL : « the airport of the Great West ? » Resulting from cooperation between airports 7
  8. 8. PLAN 1 Context and Study Stakes 2 Methodology: Game Theory 3 The “Community Game” 4 Conclusion and Prospects 8
  9. 9. Methodology: Reflexive Modelling • Using game theory to analyze real situations encounters two types of objection: • 1) Game theory formalism is too restrictive to take the complexity of reality into account. • 2) Game theory does not “claim to say what is”, because the assumptions of its models are too simplistic. • Finally, the boundaries of game theory significantly reduce its ability to help in decision making. 9
  10. 10. Methodology: Reflexive Modelling • Choosing a method: reflexive modelling (Thépot, 1998) • “Reflexive modelling claims to act further upstream on the mental representation by which the decision maker structures his schematic vision of reality” (Thépot, 1998, p. 8 and following ) • Reflexive modelling sets itself the objective of extracting from the real “a few stylized facts from which other stylized facts are deduced by using simple models of game theory which will be submitted to the discretion of the decision maker” (Thépot, 1998). 10
  11. 11. Methodology: game theory “Reflexive modelling and normative modelling” in Thépot J., (dir.), 1998, Gestion et 11 théorie des jeux. L’interaction stratégique dans la décision, ed. Vuibert
  12. 12. Methodology: Reflexive Modelling • Reflexive modelling creates space for game theory and provides an objective as well as a methodology of work: • An objective since this type of modelling claims to help the decision maker to clarify his strategic choices. • A methodology as this approach only claims to describe the nature of the strategic interactions of players so as to draw logical implications and consequences. • The aim is then less to determine the existence of solutions than to clarify the nature of the difficulties to reach them: coordination problems, conflicts of interest, impasses in cooperation, reputation effects, etc.... 12
  13. 13. Methodology: Game Theory and Prospective Approach • Proximity can be found between the approach of prospective scenario and the solution concept of game theory. • “A scenario is not the prospective reality but a means to represent it with a view to illuminating the present action in the light of possible and desirable futures” (Godet, 2004, p. 10) • The solution concept refers to the conditions imposed on the strategies of players, which if they are verified, become the solutions of the game (Guerrien, 2002). • The solution to a game, when it is reached, suggests the existence of “a viable social order”, that is to say, such a state of the world that the mutual interest of players ensures its stability. 13
  14. 14. Methodology: Game Theory and Prospective Approach • "Game theory can, on intuitive bases, ultimately identify some socially possible futures among the many conceivable scenarios” (Schmidt, 1999, p. 56). • Three situations may come up which can help the futurist to identify scenarios (Schmidt, 2000): – The first, when the solution to a game is an empty set, then the related scenario must be abandoned. – The second, when the solution is unique, then the scenario identified is the only stable state, and should be analyzed carefully. – Finally, a game may sometimes have several solutions. This can lead the futurist to make recommendations based on criteria that are external to the game itself. 14
  15. 15. Methodology: Game Theory and Prospective Approach • "The intelligence of a social situation is scarcely reduced to the understanding of a single game" (Schmidt, 2000, p. 258). • In our study, we developed three games, which each in their own way, have approached an aspect of the interactions between the players concerned by the future airport: – The focus is on the institutional dimension of the players in the “Community Game” – In the other two games, the «Airport / Airlines Game» and the « Airport in the Metropolitan Loire-Bretagne Area game (EMLB)” attention is focused on airports and their interactions with airlines. 15
  16. 16. Methodology: Game Theory and Prospective Approach • This multiplication of games is the opportunity to refine the analysis of certain types of interactions. • Each game is an independent model but none is completely cut off from the other two. – the players are the same from one game to the other – the solution to a game can affect the next game, etc... • All three games can be seen from a future oriented approach, as a metagame (Howard, 1971, Schmidt, 2000) which includes such games as many sub- games. 16
  17. 17. PLAN 1 Context and Study Stakes 2 Methodology: Game Theory 3 The “Community Game” 4 Conclusion and Prospects 17
  18. 18. The “Community Game” A – Objective: Reflecting on the conditions for cooperation between Nantes and Rennes airports Means used: - Non-cooperative game for 2 players - Solution concept used : Nash equilibrium and Schapley value 18
  19. 19. The “Community Game” A – The players A and B: two communities Objectives for A and B: A has an airport leader Increasing access through their (interregional calling) airports B has a local airport (local Maximize their attractiveness calling) 19
  20. 20. The “community game” A – the game 20
  21. 21. The “Community Game” A – Community Game Tree A Cooperation Competitive B B Cooperation Competitive Cooperation Competitive Scenario 1 Scenario 2 Scenario 3 Scenario 4 Negotiated Challenged Hierarchical Competitive Management Leadership Relationship Management 21
  22. 22. The “Community Game” A – Preference order The payoff matrix for A Assumption (1 , X) (0 , X) (3 , X) (2 , X) 22
  23. 23. The “Community Game” A – Preference order The payoff matrix for B Assumption (X , 3) (X , 2) (X , 0) (X , 1) 23
  24. 24. The “Community Game” A – The position of players with non-cooperative strategies The payoff matrix Assumption (1 , 3) (0 , 2) (3 , 0) (2 , 1) Nash equilibrium 24
  25. 25. Playing the “Community Game” • In the context of reflexive modelling of the situation, Rennes and Nantes players were offered to participate in the “community game” • This was, initially, to assess their preferences for the scenarios from political, economic and social criteria. Then, they were asked to play the game. • As the proposal failed to reach its end, we will present some results obtained with the test group (8 participants). 25
  26. 26. Playing the “Community Game” B - Experimental game Three decision criteria for A and B 1 - Political criterion Reelection of politicians 2 - Economic criterion The growth of GDP per capita 3 - Social criterion Employment (unemployment) Assumption: Three criteria weigh the same (1 / 3) in the choice of strategies 26
  27. 27. Playing the “Community Game” B – Experimental game 1st rank 4th rank (2,75 , 4,5) (-3 , 4,5) (0,25 , 4,75) (-3 , 3,25) (5,25 , -1) (1 , -2) (4,25 , -3) (4,5 , 1) Nash Equilibrium 27
  28. 28. Playing the “Community Game” B – Experimental game 1st rank 4th rank (2,75 , 4,5) (-3 , 4,5) (0,25 , 4,75) (-3 , 3,25) (5,25 , -1) (1 , -2) (4,25 , -3) (4,5 , 1) Differential between rankings constitute margins from which players can mutually adjust to (example 1) 28
  29. 29. Playing the “Community Game” B – Experimental game 1st rank 4th rank (2,75 , 4,5) (-3 , 4,5) (0,25 , 4,75) (-3 , 3,25) (5,25 , -1) (1 , -2) (4,25 , -3) (4,5 , 1) Differential between rankings constitute margins from which players can mutually adjust to (example 2) 29
  30. 30. PLAN 1 Context and Study Stakes 2 Methodology: Game Theory 3 The “Community Game” 4 Conclusion and Prospects 30
  31. 31. Conclusion and Prospects • If Game Theory concepts are not easily transferable to real cases, Reflexive Modelling offers interesting prospects to address situations in which the interactions between actors are strong. • Reflexive Modelling does not seek to determine an optimal strategy for a decision maker but rather to guide him in his decision making • Reflexive Modelling requires a dialogue between the decision maker (s) and the modeller. • We also recalled that game theory allows a futurist reading in so far as it allows to select the scenario among a set of scenarios. 31
  32. 32. Conclusion and Prospects • Finally, with respect to the subject of this conference, it appears that territorial intelligence can fully benefit from the contributions of game theory. • We will give two examples: - The first, we have experienced in our study, relies on game assessment by the players themselves with a view to clarifying their preferences, beliefs, etc... (Reflexive modelling). - The second, is related to the development of evolutionary games which, together with information technology tools, allow simulations of cooperation and competition between economic actors (Berro, Leroux, 2006). 32
  33. 33. Thank you for your attention 33

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