Sequential games with random priority

Radzik, Tadeusz; Szajowski, Krzysztof

doi:10.1080/07474949008836218

Cited by 14 publications

(11 citation statements)

References 9 publications

(2 reference statements)

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“…The payoffs of the players are determined stochastically depending on the stopping times of the players. Sakaguchi (1985a) Best versus best Enns and Ferenstein (1985) Enns and Ferenstein (1985) Sakaguchi (1985b) One selection each Majumdar (1986) Enns and Ferenstein (1990) Ohtsubo (1986) Majumdar (1985) Radzik and Szajowski (1990) Majumdar (1986) Sakaguchi (1984a,b) Sakaguchi (1992) Sakaguchi (1985a) Sakaguchi (1995a) Szajowski (1993) Radzik and Szajowski (1990) Yasuda (1985) Zero-sum Radzik and Szajowski (1990) Radzik and Szajowski (1990) Best versus best Sakaguchi (1984b) Sakaguchi (1991a) One selection each Cripps (1998) Sakaguchi (1991b Non-zero-sum Kurano et al (1980) Sakaguchi (1978b Explicit utility Szajowski andYasuda (1997) Sakaguchi (1995a) Choosing the same offer(s) Sakaguchi and Mazalov (2004) Ben Abdelaziz and Krichen (2005) Non-zero-sum Ravindran and Szajowski (1992) Best vs. best or second best Sakaguchi (1989c) One selection each Non-zero-sum Sakaguchi (1980) Sakaguchi (1985a) …”

Section: Zero-sum/explicit Utility/no Information/fixed N/one Selectimentioning

confidence: 98%

“…The case where the no information zero sum game is characterized by a random priority was considered by Radzik and Szajowski (1990). The corresponding model allows at most one acceptance for either player and if it happens that both players decide to select the same offer, a lottery is performed to assign the chosen offer to either player.…”

Section: Zero-sum/explicit Utility/no Information/fixed N/one Selectimentioning

confidence: 99%

“…Sakaguchi (1985a), assumed that the total number of offers is random. The randomness can also concern the priority of decision about the arriving offers as in Radzik and Szajowski (1990), Sakaguchi (1989a) and Sakaguchi (1991b). These games can be simultaneous or sequential.…”

Section: Introductionmentioning

confidence: 98%

See 2 more Smart Citations

Optimal stopping problems by two or more decision makers: a survey

Abdelaziz

Krichen²

2006

CMS

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Section: Zero-sum/explicit Utility/no Information/fixed N/one Selectimentioning

confidence: 98%

Section: Zero-sum/explicit Utility/no Information/fixed N/one Selectimentioning

confidence: 99%

See 1 more Smart Citation

Optimal stopping problems by two or more decision makers: a survey

Abdelaziz

Krichen²

2006

CMS

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“…In this case players have half success which is taken into account in the payoff function. Another approach assumes a priority for one decision-maker (see papers by Sakaguchi [10], Enns & Ferenstein [3], Radzik & Szajowski [6], Ravindran & Szajowski [9]) or the random priority (the paper by Fushimi [5], Radzik & Szajowski [7] and Szajowski [14]). …”

Section: Introductionmentioning

confidence: 99%

“…At each moment n one candidate is presented. The considered problem is related both to the uncertain employment considered by [12] and to the competitive optimal stopping problem with priority (see [4]) or more generally with random priority of the players (see [7], [14]). …”

Section: Introductionmentioning

confidence: 99%

Bilateral Approach to the Secretary Problem

Ramsey

Szajowski

2005

Annals of the International Society of Dynamic Games

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A mathematical model of competitive selection of the applicants for a post is considered. There are N applicants with similar qualifications on an interview list. The applicants come in random order and their salary demands are distinct. Two managers, I and II, interview them one at a time. The aim of the manager is to obtain the applicant who demands minimal salary. The candidate can be accepted only at the moment of his appearance. When both managers want to accept the same candidate, then some rule of assignment to one of the managers is applied. Any candidate hired by a manager will accept the offer with some given probability. A candidate can be hired only at the moment of his appearAu: statement is repeated.ance. At each moment n one candidate is presented. The considered problem is a generalization of the best choice problem with uncertain employment and its game version with priority or random priority. The general stopping game model is constructed. The algorithms of construction of the game value and the equilibrium strategies are given. An example is solved.

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On multilateral incomplete information decision models

Szajowski

Skarupski

2019

High Frequency

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This paper treats the decision problem related to theobservation of a Markov process by decision makers. The informationdelivered to the players is based on the aggregation of thehigh‐frequency data by some functions. Admissible strategies arestopping moments related to the available information. The paymentsare defined by the state at the time of stopping. The players' decision to stop has various effects which depend on the decisionmakers' type. The type β player's stopping decision assignsthe state of the process with chance β, and it offers thisstate to the opponent with probability 1-β. The knowledgeabout the type of the players is not public and in this way, thepayers have also different information. The details of thedescription allow to formulate the problem as a Bayesian game withsets of strategies based on the stopping times. It is an extensionof Dynkin's game related to the observation of a Markov process withthe random assignment mechanism of states to the players. Some examples related to the best choice problem (BCP) are analyzed. MSC (2000) Primary: 90D15; Secondary: 93C30.

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Sequential games with random priority

Cited by 14 publications

References 9 publications

Optimal stopping problems by two or more decision makers: a survey

Optimal stopping problems by two or more decision makers: a survey

Bilateral Approach to the Secretary Problem

On multilateral incomplete information decision models

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