Satisficing Game Theory Research Articles

Agreement options for negotiation on material location decision of housing development

PurposeDifferent housing development stakeholders need to cooperate and collaborate to perform various project activities. Housing development requires infrastructure development, which includes preparation of sand material embankment as much as ± 200,000 m3. The objectives are to find a model for agreement options and coalition, to validate the algorithms of the best fit for material locations and to determine how much the proposed agreement option was achieved. This study provides a structured methodology that can lead to systematic support system and automated negotiation for decision-making on housing development process.Design/methodology/approachAgreement option on group decision techniques was applied to determine the relative value of the alternative solutions for performing the function of project solutions. Analytical hierarchy process based on satisficing option was applied for decision process and game theory-based agent system for coalition formation. It is conducted in two stages that determine the decision preference and decision process consisting of four steps. The steps are constructing decision hierarchy, making judgment and synthesis, determining payoff optimum and analyzing the best fit option for all decision-makers.FindingsThe proposed model enables each decision-maker to select individually its coalition. It will improve the value of strategic decision. All solutions are chosen by more than one decision-maker and coalitions, where all decision-makers agree with the result. It becomes possible location for the material of a housing development. A support model enables negotiation process in group decision. Decision algorithms are based on the cooperative game theory to develop the agreement options and coalition formation. Similar research studies were carried out in this area, but this research is – to the knowledge of the authors – the first to apply the satisficing of value-based on desirable and considerable.Research limitations/implicationsThe result is limited to the first-round negotiation of collaborative decision. A trade-off algorithm among decision-maker preference is needed for negotiation process. Future research is to continue working on multi-attribute decision-making, specifically on the process of eliciting user preference models such as neural network application and value function, and on establishing expert quantitative data from qualitative description of the feature of the alternative solution. It will need the development of trade-off algorithms to analyze value of technical solution in real time.Practical implicationsThe support model can be extended to an automated negotiation and in different strategic decision on all stages of housing development.Social implicationsThe satisficing algorithm of the coalition will satisfy all stakeholders. This will reduce any potential conflict.Originality/valueCombination of value-based decision, group decision and collaborative support. Application of coalition formation for agreement options is used to select the best fit material location. It is based on satisficing game theory rather than optimization.

Cooperative sUAV Collision Avoidance Based on Satisficing Theory

The recent growth in small unmanned aerial vehicle (sUAV) applications in public and private sectors has generated a greater interest in effective collision avoidance strategies. This paper presents a cooperative collision avoidance approach for sUAV in the low-altitude uncontrolled airspace based on satisficing game theory. By incorporating both the self and cooperative preferences in making individual heading decision, satisficing framework provides a collision avoidance strategy that increases throughput while decreasing unnecessary collisions. A total of 4356 chokepoint scenarios are simulated with varying satisficing parameters, including number of sUAV agents, minimum separation, action angle, and dual utility parameters of raw preference and negotiation index. Simulation-based sensitivity analysis is conducted to find the combined effect of such parameters. The results show that performance of satisficing framework is dependent on traffic density primarily. Except for the very light traffic scenario, the minimum separation and degree of action angle affected the system efficiency the most, while dual utility parameters played crucial roles in highly conflicted scenarios. In conclusion, sUAV traffic and collision rules require an adaptive approach in regard to the traffic density, and satisficing framework can provide an effective collision avoidance strategy in a medium- to high-density traffic environment.

A Satisficing Game Theoretic Approach to Multi-Aircraft Collision Avoidance

We propose a distributed approach to multi-aircraft real-time conflict resolution based on satisficing game theory which considers reducing flight collisions and improving economic efficiency. In our conflict game model, aircraft as exclusively self-interested agent are assigned different statuses by a priority ranking mechanism proposed. According to the state of one’s own priority, they take others’ preferences into consideration to choose the most satisficing conflict resolution strategy from policy set including speed and heading modification strategies. The simulation results on the random flight scenario of two concentric circles show that our method which adopts speed and heading adjustment to avoid conflicts is promising in terms of safety and system efficiency.

A Satisficing Conflict Resolution Approach for Multiple UAVs

In this paper, we are concerned with exploring the theoretically and technically research outcomes for the conflict resolution (CR) of multiple unmanned aerial vehicles (UAVs) by using the Internet of Things technologies. We propose a satisficing algorithm to mitigate the CR problem of multiple UAVs. Specifically, we first formulate the CR problem as a game model and design strategies of the game model based on flight characteristics of UAVs. Next, a satisficing game theory is used to mitigate the formulated problem. Furthermore, required time of arrival, which is a new judgment parameter of the strategy utility, is developed to ensure that the whole system can reach a socially acceptable compromise. Simulation results verify the effectiveness and adaptability of the proposed algorithm under complex environments.

Satisficing Game Approach to Collaborative Decision Making Including Airport Management

Collaborative decision making (CDM) has been used as an essential paradigm to increase the efficiency of air traffic flow management (ATFM), including takeoff or landing operations at airports. Air traffic control (ATC) services and airlines have been involved in the current CDM, but airport management service, an important stakeholder, has not been involved yet, generally. This paper proposes a new CDM model, which is named satisficing CDM, that is based on the satisficing game theory. This model includes three main entities (ATC, airlines, and airport management) in ATFM. The complete set of functions (preference, rejectability, and selectability) is established for each of the entities. Because the delay due to ground or air holding potentially alters the takeoff or the landing order of a flight, the sequence of takeoff and landing is determined through the satisficing negotiation process. To demonstrate the utility of the developed intelligent system, experiments are run with real air traffic in the terminal area of Sao Paulo. The experimental results show the importance and effectiveness of including airport management services in CDM. The sequences of takeoff and landing determined by the proposed model mostly meet the preferences of the three stakeholders in the given real traffic scenarios.

Decision evaluation process in end-of-life systems management

In manufacturing sectors, firms are paying an increasing attention to sustainability concept with regard to their end-of-life products in order to respect environmental norms and satisfy the consumer sensitivity. This practise allows creating value by reintroducing dismantling and recovering parts and/or materials of end-of-life products into manufacturing process, or into maintenance process. Thus, deconstruction processes are developed in order to examine all activities addressing the end of life (EOL) systems to ensure its disposal according to environmental constraints when seeking an economic optimum. In this context, one of the first tasks to perform is to repatriate the EOL systems at lowest cost considering geographical optimization of treatment centers. Considering this point, the present paper proposes an evaluation and optimization approach for the withdrawal location process in the field of aircraft dismantling. Given the multitude and heterogeneity of characteristics to be taken into account, we propose to consider dismantling site location problem as multi-criteria/multi-objectives decision making problem and solve it using a new AHP-BOCR approach based on qualitative and quantitative evaluations. A bipolar structuring framework is considered to distinguish positive and negative aspects in the elicitation/evaluation process to avoid compensation and satisficing game theory is used as suitable mathematical tool for recommendation process. An experimental study is carried out to show the usefulness of the framework.

Evaluation process in end-of-life systems management using BOCR analysis

Nowadays, sustainability is an indicator or even a concept that guides many public as well as private decisions or actions. In manufacturing sectors, firms are paying an increasing attention to this concept with regards to their products once they are the end of their life; this attention is not only due to the respect of norms and laws policy makers are continuously editing to protect the environment or the sensitivity of consumers to ecological issues but also because of possibilities of new business this concept offers. Indeed, firms noticed that they can create value with the end-of-life products by dismantling them and recovering parts and/or materials that can be re-introduced into manufacturing process, into maintenance process, etc.; or just by the improvement of their image with regards to public opinion. The process of recuperating end-of-life products, known as reverse logistics, is therefore a sustainable development process which will be triggered by the consumer and consists in a series of activities; one such activity concerns withdrawal problem that consists in responding some questions such as: where the end-of-life product must be dismantled?, how to bring the product from its actual position to the dismantling place?, who is in charge of this activity?, etc. This paper considers the issue of evaluating and optimizing the withdrawal process in the field of aircraft dismantling. The withdrawal plan evaluation is formulated here as multi-criteria / multi-objectives decision making problem and solved using BOCR analysis as the structuring framework for the elicitation process and satisficing game theory as the most suitable mathematical tool for recommendation process.

Agent-Based Cooperative Decentralized Airplane-Collision Avoidance

The efficiency of the current centralized air-traffic management is limited. A next-generation air transportation system should allow airplanes (manned and unmanned) to change their flight paths during the flight without approval from a centralized en route control. Such a scheme requires decentralized peer-to-peer conflict detection and collision-avoidance processes. In this paper, two cooperative (negotiation-based) conflict-resolution algorithms are presented: iterative peer-to-peer and multiparty algorithms. They are based on high-level flight-plan variations using evasion maneuvers. The algorithms work with a different level of coordination autonomy, respect realistic assumptions of imprecise flight execution (integrating required navigation performance), and work in real time, where the planning and plan-execution phases interleave. Both algorithms provide a resolution in a 4-D domain (3-D space and time). The proposed algorithms are evaluated experimentally, and their quality is studied in comparison with a state-of-the-art agent-based method-the satisficing game theory algorithm.

Attitude Adaptation in Satisficing Games

Satisficing game theory offers an alternative to classical game theory that describes a flexible model of players' social interactions. Players' utility functions depend on other players' attitudes rather than simply their actions. However, satisficing players with conflicting attitudes may enact dysfunctional behaviors, which results in poor performance. We present an evolutionary method by which a population of players may adapt their attitudes to improve payoff. In addition, we extend the Nash-equilibrium concept to satisficing games, showing that the method leads players toward the equilibrium in their attitudes. We apply these ideas to the stag hunt--a simple game in which cooperation does not easily evolve from noncooperation. The evolutionary method provides two major contributions. First, satisficing players may improve their performance by adapting their attitudes. Second, numerical results demonstrate that cooperation in the stag hunt can emerge much more readily under the method we present than under traditional evolutionary models.

Satisficing Game Theory for Conflict Resolution and Traffic Optimization

In the current, centralized approach to Air Traffic Control (ATC) air traffic controllers are responsible for the safe and efficient flow of aircraft. This situation would change with the introduction of Airborne Self-Separation as a distributed and scalable approach to ATC. The major technological challenge that must be tackled to make Airborne Self-Separation a viable alternative to the traditional controller-based approach is to devise a safe and reliable technology to solve conflicts and improve global performances in an uncontrolled environment. In this paper we introduce an algorithm that applies Satisficing Game Theory (SGT) to solve conflicts in the framework of an overall optimization of the traffic flow. This decentralized and cooperative algorithm is inspired by the work presented in [1]. The SGT provides a strategy that permits decision-makers to reach a compromise in the interest of achieving both individual and group goals, implementing altruistic behavior. The paper presents the first results we collected by running a software tool which simulates the behavior of the SGT algorithm in a 3D environment, using air traffic samples provided by the Italian air traffic service provider (ENAV). These results are the starting point of a further enquiry to explore the actual impact of the introduction of such a technology into a realistic ATC environment.

Satisficing negotiations

Negotiation procedures that are founded on the doctrine of individual rationality, where each participant is committed to maximizing its own satisfaction, are limited in their ability to accommodate the interests of others, and therefore, may unnecessarily constrain the negotiability of a decision maker, particularly in cooperative environments. Satisficing game theory provides a distinct alternative to the hyperrationality of conventional rational choice by waiving reliance on the individual rationality premise and offering an approach to negotiatory decision making that is based on a well-defined mathematical notion of satisficing, or being good enough, that permits the modeling of complex interrelationships between agents. This approach provides a mechanism to compute the attitude, or degree of conflict or contentedness, of the negotiators. Examples illustrate both single-round and multiround satisficing negotiation protocols

Social Utility Functions—Part II: Applications

Social utilities account for agent preferences and, thus, can characterize complex interrelationships, such as cooperation, compromise, negotiation, and altruism, that can exist between agents. Satisficing game theory, which is based on social utilities, offers a framework within which to design sophisticated multiagent systems. Key features of this approach are: a) an N-agent system may be represented by a 2N-dimensional Bayesian network, called a praxeic network; b) the theory accommodates a notion of situational altruism (a willingness to defer to others in a controlled way if so doing would actually benefit others under the condition that others wish to take advantage of such largesse); and c) satisficing games admits a protocol for effective negotiation between agents who, though interested in their own welfare, are also willing to give some deference to others. Three applications are presented. The first two involve well-known two-person games: the Prisoner's Dilemma and the Battle of the Sexes, and the third is a simulated uninhabited aerial vehicle scenario.

A satisficing game theory approach for group evaluation of production units

The problem under consideration in this paper is that of analysing the performance of a production unit in two directions: resource utilization versus output perfomance on the one hand and inter-unit comparison (within-group evaluation) on the other hand, all this subjected to possible subjective intervention of a decision maker or group of decision makers (DMs). A well known method that deals mainly with the second point (without intervention of DMs) of this problem which is widely covered in the literature is the so called data envelopment analysis (DEA). The point of view that will be expressed in this paper can be thought of as complementary to the DEA approach giving a more complete analysis in terms of the weak points of units identification and DMs' recommendations. The performance of each decision unit is evaluated through the so called satisfiability functions in the framework of satisficing game theory.

Games Machines Play

Individual rationality, or doing what is best for oneself, is a standard model used to explain and predict human behavior, and von Neumann–Morgenstern game theory is the classical mathematical formalization of this theory in multiple-agent settings. Individual rationality, however, is an inadequate model for the synthesis of artificial social systems where cooperation is essential, since it does not permit the accommodation of group interests other than as aggregations of individual interests. Satisficing game theory is based upon a well-defined notion of being good enough, and does accommodate group as well as individual interests through the use of conditional preference relationships, whereby a decision maker is able to adjust its preferences as a function of the preferences, and not just the options, of others. This new theory is offered as an alternative paradigm to construct artificial societies that are capable of complex behavior that goes beyond exclusive self interest.