Session MA1 - Théorie des jeux I / Game Theory I
Day Monday, May 04, 2009 Room St-Hubert President Fouad El Ouardighi
Presentations
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10h30 AM- 10h55 AM |
When is it Optimal to Ignore the Threat of a Competitive Entry? |
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Olivier Rubel, University of California at Davis, Graduate School of Management, One Shields Avenue, Davis, CA, USA, 95616 The piecewise deterministic optimal control framework is used to analyze a dynamic model where a monopolist is not sure about the exact entry date of a possible competitor. Combining simultaneously stochastic entry and finite time horizon I identify the optimal feedback pricing strategies before and after the entry occurred for players. Managerial conclusions are derived. |
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10h55 AM- 11h20 AM |
A Differential Game of Supply Chain Coordination and Horizontal Competition |
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Fouad El Ouardighi, ESSEC Business School, Logistics, Production and Service, Cergy Pontoise, France Pietro de Giovanni, ESSEC Business School, Ph.D. Program, BP 105, Cergy Pontoise, France, 95021 In this paper we consider two supply chains, each consisting of one manufacturer and one retailer. The supply chains compete for market demand both on price and advertising goodwill. The paper analyzes the players' dynamic optimal policies on inventory management, retail price, and advertising effort. We compare the possible outcomes of the game under wholesale price and revenue-sharing contracts. |
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11h20 AM- 11h45 AM |
Capacity Investments in a Stochastic Dynamic Game: Good News Principle |
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Talat Genc, University of Guelph, Economics, Guelph, ON, Canada Georges Zaccour, GERAD, HEC Montréal, Marketing, 3000, chemin de la Côte-Sainte-Catherine, Montréal, Québec, Canada, H3T 2A7 We study dynamic game with capacity accumulation under demand uncertainty. We find that the firms may invest at a higher level in the open-loop equilibrium than in the closed-loop equilibrium. We also observe that firms may invest more as demand volatility increases and they invest as if good news will unfold in the future. |
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11h45 AM- 12h10 PM |
Cooperative Unmanned Aerial Vehicles for Target Search |
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Jean Berger, Defence Research Development Canada, Decision Support Technology Section, 2459, boul. Pie-XI nord, Val-Bélair, Québec, Canada, G3J 1X5 In this work, we extend previous work reported on multi-UAV target search by learning multi-agent coordination, considering an open-loop with feedback decision model. The approach first relies on a new information-theoretic co-evolutionary algorithm to solve cooperative search path planning over receding horizons, providing agents with mutually adaptive and self-organizing behavior. |