Evidence in Games and Mechanisms

With the population growth and the social economy development, there is a consensus among scholars and decision makers that tackling global environmental problems and promoting sustainable development requires a joint effort of many players (countries). Game theory has been used widely to study these economical cooperation problems. Most of these contributions focus on showing the efficiency of cooperation. This paper aims to the mechanism design of promoting long run cooperation among players for environmental management in wider situation by means of dynamic programming and game theory. The mechanism of promoting cooperation designed in every stage provides a feasible and fair cost vector for every player, which indicates the possibility and stability of cooperation. This self-incentive process of cooperation provides theoretical basis for cooperative environmental management.

Machine learning and game theory are two important directions of AI. The former usually assumes data is independent of the models to be learned; the latter usually assumes agents are fully rational. In many modern Internet applications, like sponsored search and crowdsourcing, the two basic assumptions are violated and new challenges are posed to both machine learning and game theory. To better model and study such applications, we need to go beyond conventional machine learning and game theory (mechanism design), and adopt a new approach called mechanism learning with mechanism induced data. Specifically, we propose to learn a behavior model from data to describe how real agents play the complicated game, instead of making the full-rationality assumption. Then we propose to optimize the mechanism by using the learned behavior models to predict the future behaviors of agents in response to the new mechanism. Because the above process couples mechanism learning and behavior learning in a loop, new algorithms and theories are needed to perform the task and guarantee the asymptotical performance. As shown in this paper, there are many interesting research topics along this direction, many of which are still open problems, waiting for researchers in our community to deeply investigate.

과거 우리나라 농촌개발모형인 새마을운동의 핵심정신인 ‘자조(Self-Help)’를 기반으로 국제개발협력사업에서 협력국 주민들의 자부담을 요구하는 새마을운동형 농촌개발사업은, 최근 다자 및 양자원조 기관들의 관심을 받기 시작하고 있다. UNDP는 최근 연구에서 새마을운동형 농촌개발 사업을 현장에 적용하기 위한 국가 및 지역전략, 협력국가 선정기준, 시행 메커니즘을 제시하였으나, 주민의 참여를 유인하기 위한 구체적이고 정량적 가이드라인은 제시하지 못하고 있다. 본 연구는 逆게임이론(Reverse Game Theory)인 메커니즘 디자인(Mechanism Design)을 이용하여, 경쟁을 통해 주민들에게 참여유인을 제공하는 자부담 수준에 따른 보상수준을 계량화하고 이를 표로 제시함으로써, 사업형성이나 시행단계에서 용이하게 적용할 수 있도록 하였다. 연구결과, 개인합리성과 단체합리성을 만족하여 주민의 자발적 참여를 유인하는 조건들은 1) 주민의 참여를 유인하기 위한 추가적 보상액의 비율은, 공여기관이 부담한 금액에 대한 주민의 총(현물 및 현금)자부담의 상대적 비율과 주민의 현물 자부담의 상대적 비율의 합보다 크게 결정되어야 하며, 2) 수혜자의 현금 및 현물 자부담 비중은 50%를 넘지 않도록 하여야 한다는 것이다. 이러한 조건을 만족하는 보상수준 및 참여도의 조합들은 게임이론의 핵(核; Core)에 해당하며, 이들 가운데 주민들간의 갈등을 최소화하는 조합은 중핵(中核; Nucleolus)으로써, 주민은 현물 또는 현금으로 약 20%의 사업비를 자조(Self-Help) 비용으로 부담하는 것이 바람직하다는 결론에 이르렀다. 이러한 결과는 기 시행되었던 새마을운동 사업에서의 추천 자부담율(20%) 및 실제 자부담율(49%)과 모순되지 않고 있음을 발견하였다.Many rural development projects were unsuccessful due to lack of voluntary participation by recipient villagers. The objectives of this study are: 1) To provide a quantitative guideline on reward level to induce villagers’ participation, 2) To integrate the spirit of Self-Help and a competition process into the incentive mechanism design. It is found that such participatory mechanisms can be devised so that the outcome is in the Core. To achieve the objective, Mechanism Design is used and the derived conditions are: 1) The size of reward has to be greater than the relative size of cash and in-kind contribution to the size of monetary benefit, 2) The contribution ratio from villagers in cash or in-kind should not exceed 50%. A reward assignment table is proposed for easier application of the result in the field, along with recommended participation level of 20% implied by Nucleolus.

An efficient peer grading mechanism is proposed for grading the multitude of assignments in online courses. This novel approach is based on game theory and mechanism design. A set of assumptions and a mathematical model is ratified to simulate the dominant strategy behavior of students in a given mechanism. A benchmark function accounting for grade accuracy and workload is established to quantitatively compare effectiveness and scalability of various mechanisms. After multiple iterations of mechanisms under increasingly realistic assumptions, three are proposed: Calibration, Improved Calibration, and Deduction. The Calibration mechanism performs as predicted by game theory when tested in an online crowd-sourced experiment, but fails when students are assumed to communicate. The Improved Calibration mechanism addresses this assumption, but at the cost of more effort spent grading. The Deduction mechanism performs relatively well in the benchmark, outperforming the Calibration, Improved Calibration, traditional automated, and traditional peer grading systems. The mathematical model and benchmark opens the way for future derivative works to be performed and compared.

Mechanism design is a subfield of microeconomics and game theory. It considers how to implement good system-wide solutions to problems that involve multiple self-interested agents [1]. In 2007, the Nobel Prize in economics was awarded to Leonid Hurwicz, Eric Maskin, and Roger Myerson “for having laid the foundations of mechanism design theory.” This indicates the importance and popularity of mechanism design in various areas of applied economics as well as market-driven applications. For instance, mechanism design has been extensively studied in practical engineering problems, such as electronic market design, distributed scheduling, and radio resource allocation.

Essential Microeconomics is designed to help students deepen their understanding of the core theory of microeconomics. Unlike other texts, this book focuses on the most important ideas and does not attempt to be encyclopedic. Two-thirds of the textbook focuses on price theory. As well as taking a new look at standard equilibrium theory, there is extensive examination of equilibrium under uncertainty, the capital asset pricing model, and arbitrage pricing theory. Choice over time is given extensive coverage and includes a basic introduction to control theory. The final third of the book, on game theory, provides a comprehensive introduction to models with asymmetric information. Topics such as auctions, signaling and mechanism design are made accessible to students who have a basic rather than a deep understanding of mathematics. Examples and diagrams are used to illustrate issues as well as formal derivations.

One of the biggest challenges facing behavioral economics is the lack of a single theoretical framework that is capable of directly utilizing all types of behavioral data. One of the biggest challenges of game theory is the lack of a framework for making predictions and designing markets in a manner that is consistent with the axioms of decision theory. An approach in which solution concepts are distribution-valued rather than set-valued (i.e. equilibrium theory) has both capabilities. We call this approach Predictive Game Theory (or PGT). This paper outlines a general Bayesian approach to PGT. It also presents one simple example to illustrate the way in which this approach differs from equilibrium approaches in both prediction and mechanism design settings.

The aim of our research is to understand and automate the mechanisms by which language can emerge among artificial, knowledge-based and rational agents. We want to design and implement agents that, upon encountering other agent(s) with which they do not share an agent communication language, are able to initiate creation of, and further are able to evolve and enrich, a mutually understandable communication language. Our research is supported by the principled methodology of designing rational, socially competent artificial agents based on Bayesian probability and decision theories, and on the research in linguistics and cognitive psychology that addresses the issues of function, mechanisms, development, and evolutionary history of natural languages. In our work, we express some of the key insights obtained in linguistics and cognitive science in formal terms of decision theory and game-theoretic. mechanism design. We propose that the evolution of an agent communication language can be accomplished by the mechanism of negotiation, developed in economics and game theory, and automated in recent work in artificial intelligence. Negotiation is suitable because it can be mapped to settings in which rational interacting agents could use communication for their mutual, yet selfish, benefits. The agents can make mutually beneficial agreements that will allow efficient communication, but they have a conflict of interest about which language constructs to use each would prefer a communication language that is easier and less costly to use from their own individual perspective.

Buyers requiring large parcels of land for development purposes engage several owners in a bilateral trade seeking monetary payment in exchange for land – a business transaction most often referred to in the literature as the problem of land assembly. To avoid the holdout problem which is a typical consequence of such negotiations necessitates a good pricing strategy that meets the subjective valuation considerations of the owners and protecting property rights to warrant a fair and efficient outcome. Several approaches have been proposed in the literature that includes contributions from game theory in the form of Nash bargaining, Bayesian theory for incomplete information, auction theory and Mechanism Design which have individually enriched this field and proposed credible solutions. In this paper, we consider a setting that has a single buyer and N sellers. We take a Mechanism Design approach to study the assembly problem in a utilitarian framework, where we associate risk-averse utility functions with the sellers. Given a set of reserve prices reported by sellers, and their risk-aversion behaviour, we seek an incentive-compatible mechanism that simultaneously maximizes the sum of individual expected utilities while delivering a Pareto optimal per-seller penalty-reward structure. We show how this mechanism, inspired and adapted from the actuarial Risk Exchange concept in the Insurance industry, can be fruitfully applied to the land assembly problem, yielding an efficient and optimal solution to the holdout problem, while making very minimal demands on knowledge of sellers valuations. The working of the mechanism is illustrated with a simple example.

China's Growth Enterprise Market has just started, because of the characteristics of the market itself, its risk is much higher than the ordinary securities investment markets. The risk of China's Growth Enterprise Market is can be reflected in many aspects, one of which from the investors is mainly caused by the excess of retail investors. To change this situation, this article, based on the principle of mechanism design in game theory, makes a pricing analysis of the commission rate of different types of investors and achieves the risk management of access system for the GEM market investors on the premise of ensuring the maximal interest of the securities companies.

This paper focuses on the significance of game balance in games and explores the application of game theory concepts for designing and analyzing balanced gameplay. When analyzing instances of games, the paper initially presents the renowned prisoner’s dilemma, a prominent problem in game theory, and delves into diverse strategies along with their corresponding advantages, thereby enabling readers to appreciate the captivating essence of game theory. After that, the paper respectively mentions two individual cases from two different forms of games. The well-known game Rock-Paper-Scissors is a simple strategy game. FPS (First Person Shooter) game is a sort of video game that is a complex strategy game. In analyzing this type of game, the paper draws images to show the imbalance in the game. In the end, the article puts forward the prospect that game theory can contribute to game design. The approach adopted in this study integrates existing research in game theory with practical insights from game design, without delving into extensive theoretical derivations or complex formulas.

Chapter 9 - Cyberphysical Security Methods

Agents’ speculation behaviors are series problems which need to be solved. Through mathematical models and game theory, this paper analyzes optimal incentive contracts between principals and agents under asymmetric information condition in order to solve the problems in establishing incentive mechanism for agents. The relationship between incentive and risk is discussed and the best equilibrium between them is given. Supervision mechanism is introduced and analyzed in the design of incentive mechanism for agents. It expands the theoretical frame for incentive mechanism. The results are as follows: Supervision mechanism is related and complementary with incentive mechanism. Both can encourage or guide the agents to work hard towards common goals. Therefore, the function of the incentive mechanism and the supervision mechanism should be considered simultaneously in the design of incentive contracts for agents. It helps to prevent agents from speculating. Introduction of supervision mechanism into incentive mechanism not only results in theoretical innovation, but also has great application value in practice.Keywordsasymmetric informationincentive mechanismmonitoring mechanismgame theorymathematical models

This dissertation presents novel approaches to modeling and analyzing security and resource allocation in mobile ad hoc networks (MANETs). The research involves the design, implementation and simulation of different models resulting in resource sharing and security’s strengthening of the network among mobile devices. Because of the mobility, the network topology may change quickly and unpredictably over time. Moreover, data-information sent from a source to a designated destination node, which is not nearby, has to route its information with the need of intermediary mobile nodes. However, not all intermediary nodes in the network are willing to participate in data-packet transfer of other nodes. The unwillingness to participate in data forwarding is because a node is built on limited resources such as energy-power and data. Due to their limited resource, nodes may not want to participate in the overall network objectives by forwarding data-packets of others in fear of depleting their energy power. To enforce cooperation among autonomous nodes, we design, implement and simulate new incentive mechanisms that used game theoretic concepts to analyze and model the strategic interactions among rationale nodes with conflicting interests. Since there is no central authority and the network is decentralized, to address the concerns of mobility of selfish nodes in MANETs, a model of security and trust relationship was designed and implemented to improve the impact of investment into trust mechanisms. A series of simulations was carried out that showed the strengthening of security in a network with selfish and malicious nodes. Our research involves bargaining for resources in a highly dynamic ad-hoc network. The design of a new arbitration mechanism for MANETs utilizes the Dirichlet distribution for fairness in allocating resources. Then, we investigated the problem of collusion nodes in mobile ad-hoc networks with an arbitrator. We model the collusion by having a group of nodes disrupting the bargaining process by not cooperating with the arbitrator. Finally, we investigated the resource allocation for a system between agility and recovery using the concept of Markov decision process. Simulation results showed that the proposed solutions may be helpful to decision-makers when allocating resources between separated teams.

Studying the research results by Nobel prize-winning economists is a fundamentally important task for determining the most promising areas of development of Russian economic science. The author traces the connections between all these works and their predecessors’ work, many of whom were also awarded the Nobel prize in economics. Three lines of development of the predecessors’ achievements are identifid: information asymmetry, limited rationality, the design of market mechanism and new institutionalism. The article does not address the problems of auction theory related to its formal justifiation, which is part of mathematical economics and game theory. However, it is noted that this is an essential part of the laureates’ achievements. The article’s main conclusions are that the prize received for “improving the theory of auctions” fis into the broader economic research context. The winners solved the problems of maintaining free competition and reducing the market’s likelihood of monopolization. The author pays special attention to the results of the empirical analysis of actually implemented auctions. This analysis is divided into three parts, corresponding to the three stages of each auction: starting problems (distrust, the reputation of participants, etc.), the course of the auction (behaviour of participants and results, in particular, the “winner’s curse”.