STRATEGIC INTERACTIONS AND NEGATIVE OIL PRICES

This paper argues on theoretical grounds that the negative oil prices event on April 20, 2020, was mainly due to the strategic interactions among some active traders on both sides of the futures contract. We present a three-player game of futures trading in which a continuum range of negative price can be supported as (strong) Nash equilibrium, yet none of those constitutes an [Formula: see text]-equilibrium originally developed by Ma (2009). We further propose the notion of coalition-with-side-payment as a solution concept for the environment where strategic interactions and transfer payments among players are allowed. Our model captures the mechanism underlying futures price manipulation, and its predictions largely agree with the observations on that day, which are beyond the scope of demand–supply and physical delivery narratives.

SOD2G: A Study on a Social-Engineering Organizational Defensive Deception Game Framework through Optimization of Spatiotemporal MTD and Decoy Conflict

Existing moving target defense (MTD) and decoy systems are conceptually limited in avoiding and preventing attackers’ social-engineering real-time attacks by organization through either structural mutations or induction and isolation only using static traps. To overcome the practical limitations of existing MTD and decoy and to conduct a multi-stage deception decision-making in a real-time attack-defense competition, the current work presents a social-engineering organizational defensive deception game (SOD2G) as a framework, consi dering hierarchical topologies and fingerprint characteristics by organization. The present work proposed and applied deception concepts and zero-sum-based two-player game models as well as attacker and defender decision-making process based on deceivable organizational environments and vulnerability information. They were designed in consideration of limited organizational resources so that they could converge in the positive direction to secure organizational defender dominant share and optimal values of the defender deception formulated by both scenario and attribute. This framework could handle incomplete private information better than existing models and non-sequentially stratified, and also contributed to the configuration of the optimal defender deception strategy. As the experimental results, they could increase the deception efficiency within an organization by about 40% compared to existing models. Also, in the sensitivity analysis, the proposed MTD and decoy yielded improvements of at least 60% and 30% in deception efficiency, respectively, compared to the existing works.

Multi-Player Evolutionary Game of Network Attack and Defense Based on System Dynamics

We formalize the adversarial process between defender and attackers as a game and study the non-cooperative evolutionary game mechanism under bounded rationality. We analyze the long-term dynamic process between the attacking and defending parties using the evolutionary stable strategies derived from the evolutionary game model. First, we construct a multi-player evolutionary game model consisting of a defender and multiple attackers, formally describe the strategies, and construct a three-player game payoff matrix. Then, we propose two punishment schemes, i.e., static and dynamic ones. Moreover, through the combination of mathematical derivation with simulation, we obtain the evolutionary stable strategies of each player. Different from previous work, in this paper, we consider the influence of strategies among different attackers. The simulation shows that (1) in the static punishment scheme, increasing the penalty can quickly control the occurrence of network attacks in the short term; (2) in the dynamic punishment scheme, the game can be stabilized effectively, and the stable state and equilibrium values are not affected by the change of the initial values.

Does Protest “Distract” Athletes From Performing? Evidence From the National Anthem Demonstrations in the National Football League

While there is a long tradition of activism within sport, a popular criticism of athlete protest is that it is a “distraction” that hinders on-field performance. The widespread demonstrations against racial injustice in 2017 among players in the National Football League (NFL) provided an opportunity to test this “distraction hypothesis.” Using data drawn from multiple sources, we first explored which factors predicted player protest, finding that Black players and those playing for underdogs were more likely to protest. Then, using a series of analyses at the player-game level ( n = 19,051) and the team-game level ( n = 512), we tested the assertion that protest is detrimental to individual or team performance, finding no evidence for a distraction effect. The results of this study allow us to better understand social factors that may affect athletic performance or constrain athlete activism.

On the power of lookahead in single-player PuyoPuyo

PuyoPuyo is one of the Tetris-type games, which is dealt with as a single-player game in this paper. The player has a winning strategy if the player can keep playing the game infinitely on a gameboard of a constant height. In this paper, we consider how lookahead of input pieces affects the existence of winning strategies in PuyoPuyo, and show conditions that the player cannot win even with lookahead. First, we show the number of colors sufficient to make the player lose on the gameboard of width w when the number of lookahead pieces is m. Next, we show that ten and twenty-six colors are sufficient to make the player lose on the gameboards of width two and three, respectively, no matter how large the number of lookahead pieces is.

Multi-party referential communication in complex strategic games

Verbal communication is an ubiquitous aspect of human interaction occurring in many contexts; however, it is primarily studied in the limited context of two people communicating information. Understanding communication in complex, multi-party interactions is both a scientific challenge for psycholinguistics and an engineering challenge for creating artificial agents who can participate in these richer contexts. We adapted the reference game paradigm to an online 3-player game where players refer to objects in order to coordinate selections based on the available utilities. We ran games with shared or individual payoffs and with or without access to language. Our paradigm can also be used for artificial agents; we trained reinforcement learning-based agents on the same task as a comparison. Our dataset shows the same patterns found in simpler reference games and contains rich language of reference and negotiation.

Exploiting symmetries of high-level Petri games in distributed synthesis

Distributed Synthesis is the problem of automatically generating correct controllers for individual agents in a distributed system. Petri games model this problem by a game between two teams of players on a Petri net structure. Under some restrictions, Petri games can be solved by a reduction to a two player game. The concept of symmetries in Petri nets is closely related to high-level representations of Petri games. Applying symmetries to the states in the two-player game results in a significant state space reduction. We give an overview about (high-level) Petri games and the application of symmetries in this setting. We present ongoing work aiming to concisely describe solutions of Petri games by a high-level representation.

Nonzero-Sum Stochastic Games and Mean-Field Games with Impulse Controls

We consider a general class of nonzero-sum N-player stochastic games with impulse controls, where players control the underlying dynamics with discrete interventions. We adopt a verification approach and provide sufficient conditions for the Nash equilibria (NEs) of the game. We then consider the limiting situation when N goes to infinity, that is, a suitable mean-field game (MFG) with impulse controls. We show that under appropriate technical conditions, there exists a unique NE solution to the MFG, which is an ϵ-NE approximation to the N-player game, with [Formula: see text]. As an example, we analyze in detail a class of two-player stochastic games which extends the classical cash management problem to the game setting. In particular, we present numerical analysis for the cases of the single player, the two-player game, and the MFG, showing the impact of competition on the player’s optimal strategy, with sensitivity analysis of the model parameters.

Government's Policy on Controlling the Covid-19 Virus Based on the Game Theory Approach: Closing Jobs or Purchasing Vaccines

Background: The tools to control COVID-19 virus and this epidemic have been tested in all countries and at different levels. At the community level, they include observing hygienic principles, such as observing social distance, wearing masks, washing hands, observing cleanliness, observing personal belongings, and etc. Also at the macro level, governments have taken measures to combat the virus, such as closing cities, purchasing vaccines hygiene training. Given the high costs of closing cities and purchasing vaccines for governments, they may be willing to select and use a combination of them to control the virus. Considering these 2 factors as 2 competitors in the effectiveness of COVID-19 control, this study sought to find an equilibrium point to control the virus. Methods: An infinite 2-player game was defined by considering the number of cities closed per person-day and the number of vaccine purchased per person, both of which have continuous and infinite space. On the other hand, a significant basic criterion for governments can be the cost and number of patients with the disease. Hence, the game was defined based on 2 criteria. A case study was also solved for the sake of clarity. Results: The government must close offices for at least 12 days and inject 2 doses of the vaccine to about 28 million people in order to achieve its goal of reducing costs and reducing the incidence of the disease. Conclusion: By solving the proposed model, it was found that for the initial control of the disease, the purchase and injection of vaccines can be more effective, but in order to further reduce and control the disease, it is better to close jobs. Analyses also showed that governments that are less willing to spend money on disease control could close jobs.