On the Stackelberg strategy in nonzero-sum games

Simaan, Marwan A.; Cruz, J.B.

doi:10.1007/bf00935665

Cited by 654 publications

(187 citation statements)

References 9 publications

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“…The Stackelberg games [28][29][30] are typical of decision making games. Since Murphy's [31] Administration Decision Game developed to teach quantitative thinking and planning, researchers have been designing decision making tutoring games [32][33][34] whose context is usually real life.…”

Section: Non-optimal Decision Makingmentioning

confidence: 99%

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Lu-Lu: A framework for collaborative decision making games

Daylamani-Zad

Angelides

Agius

2016

Decision Support Systems

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This paper proposes Lu-Lu as an add-on architecture to open MMOGs and social network games, which has been developed to utilise a key set of ingredients that underline collaborative decision making games as reported within the research literature: personalisation, team matching, non-optimal decision making, leading, decisiveness index, scoring, levelling, and multiple stages. The implementation of Lu-Lu is demonstrated as an add on to the classic supply chain beer game, including customisation of Lu-Lu to facilitate information exchange through the Facebook games platform, e.g. Graph API and Scores API. Performance assessment of Lu-Lu using Behaviour Driven Development suggests a successful integration of all key ingredients within Lu-Lu's architecture, yielding autonomous behaviour that improves both player enjoyment and decision making.

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Section: Non-optimal Decision Makingmentioning

confidence: 99%

“…Stackelberg games [28,29] are considered the natural choice for oligopolistic markets and security domains and are the backbone of security systems such as ARMOR, IRIS, and GUARDS whose decision aim is resource allocation. Stackelberg games are also widely used in supply chain management [37,38].…”

Section: Leadingmentioning

confidence: 99%

Lu-Lu: A framework for collaborative decision making games

Daylamani-Zad

Angelides

Agius

2016

Decision Support Systems

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“…Under the assumption that these DMs do not have motivation to cooperate mutually, the Stackelberg solution [39,3,37,17] is adopted as a reasonable solution for the situation. On the other hand, in the case of a project selection problem in the administrative office of a company and its autonomous divisions, the situation that these DMs can cooperate with each other seems to be natural rather than the noncooperative situation.…”

Section: Introductionmentioning

confidence: 99%

Interactive Fuzzy Programming for Stochastic Two-level Linear Programming Problems through Probability Maximization

Sakawa

Matsui²

2013

AIR

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ForewordIn this paper, we focus on stochastic two-level linear programming problems involving random variable coefficients both in objective functions and constraints. Using the concept of chance constraints, stochastic constraints are transformed into deterministic ones. Following the probability maximization model, the minimization of each stochastic objective function is replaced with the maximization of the probability that each objective function is less than or equal to a certain value. Under some appropriate assumptions for distribution functions, the formulated stochastic two-level linear programming problems are transformed into deterministic ones. Taking into account vagueness of judgments of the decision makers, we present interactive fuzzy programming. In the proposed interactive method, after determining the fuzzy goals of the decision makers at both levels, a satisfactory solution is derived efficiently by updating the satisfactory degree of the decision maker at the upper level with considerations of overall satisfactory balance among both levels. It should be emphasized here that the transformed deterministic problems for deriving an overall satisfactory solution can be easily solved through the combined use of the bisection method and the phase one of the simplex method. An illustrative numerical example is provided to demonstrate the feasibility of the proposed method.-iii - AbstractThis paper considers stochastic two-level linear programming problems. Using the concept of chance constraints and probability maximization, original problems are transformed into deterministic ones. An interactive fuzzy programming method is presented for deriving a satisfactory solution efficiently with considerations of overall satisfactory balance.

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“…In this setting, the evader's strategy should be chosen carefully, considering the worst-case (from the evader's point of view) response of the pursuer. Rational players in this game will choose a Stackelberg strategy with the evader as a leader [6].…”

Section: Introductionmentioning

confidence: 99%

Incremental Sampling-Based Algorithms for a Class of Pursuit-Evasion Games

Karaman

2010

Springer Tracts in Advanced Robotics

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Pursuit-evasion games have been used for modeling various forms of conflict arising between two agents modeled as dynamical systems. Although analytical solutions of some simple pursuit-evasion games are known, most interesting instances can only be solved using numerical methods requiring significant offline computation. In this paper, a novel incremental sampling-based algorithm is presented to compute optimal open-loop solutions for the evader, assuming worst-case behavior for the pursuer. It is shown that the algorithm has probabilistic completeness and soundness guarantees. As opposed to many other numerical methods tailored to solve pursuit-evasion games, incremental sampling-based algorithms offer anytime properties, which allow their real-time implementations in online settings.

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On the Stackelberg strategy in nonzero-sum games

Cited by 654 publications

References 9 publications

Lu-Lu: A framework for collaborative decision making games

Lu-Lu: A framework for collaborative decision making games

Interactive Fuzzy Programming for Stochastic Two-level Linear Programming Problems through Probability Maximization

Incremental Sampling-Based Algorithms for a Class of Pursuit-Evasion Games

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