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The reliability of each component in a system plays a crucial role, as any malfunction can significantly reduce the system's overall lifespan. Optimizing the arrangement and sequence of heterogeneous components with varying lifespans is essential for enhancing system stability. This paper addresses the redundancy allocation problem (RAP) by determining the optimal number of components in each subsystem, considering their sequence, and optimizing multiple criteria such as reliability, cost uncertainty, and weight. A novel approach is introduced, incorporating a switching mechanism that accommodates both correct and defective switches. To assess reliability benefits, Markov chains are employed, while cost uncertainty is evaluated using the Monte-Carlo method with risk criteria such as percentile and mean-variance. The problem is solved using a modified genetic algorithm, and the proposed method is benchmarked against alternative approaches in similar scenarios. The results demonstrate a significant improvement in the Model Performance Index (MPI), with the best RAPMC solution under a mixed strategy achieving an MPI of 0.98625, indicating superior model efficiency compared to previous studies. Sensitivity analysis reveals that lower percentiles in the cost evaluations correlate with reduced objective function values and mean-variance, confirming the model's robustness in managing redundancy allocation to optimize reliability and control cost uncertainties effectively.

Changes in the animals' environment often impact on their behavior and the way they communicate. Particularly in spiders, living on webs or not is a determining factor. While the Lycosidae family predominantly comprises wandering spiders, only a few species inhabit webs. Aglaoctenus oblongus (C.L. Koch 1847) challenges this norm, as it has been found both in webs and wandering, suggesting a previously undocumented mixed strategy. This study aims to: (1) describe the sexual behavior of A. oblongus under laboratory conditions and (2) utilize phenological data to elucidate when and where mating occurs. Sexual encounters were observed within and outside webs, with minimal differences noted between them. Courtship was characterized by groping and leg shaking performed by the males. Copulation was lengthy (near to seven hours), featuring an irregular pattern of palpal insertions, and culminating in a backward dismount. Individuals showed a mixed life history, with the spiders most often found in webs being females with eggs. Both sexes were found throughout the year, with a peak in autumn. We compare the sexual characteristics of this species with that of A. lagotis (also belonging to the Sosippinae subfamily), the only other wolf spider studied to date that exclusively inhabits webs. [ABSTRACT FROM AUTHOR]

Focusing on the extreme points of the solution sets of matrix two-person games, we propose the notions of characteristic sets and characteristic numbers. The characteristic sets (resp., the characteristic numbers) are the sets (resp., the numbers) of the extreme points of the solution set of the game and the optimal solution sets of the players. These concepts allow us to measure the complexity of the game. The larger the characteristic numbers, the more complex the game is. Among other things, we obtain upper bounds for the characteristic numbers and give a novel geometric construction. By the construction, we get useful descriptions of the optimal strategy set of each player of a game given by any nonsingular square matrix. Namely, the investigation of the geometry the just-mentioned sets reduces to computing or studying certain simpler sets. We also formulate several open problems. [ABSTRACT FROM AUTHOR]

Industrialization and increased energy use are leading to a greater influence of environmental and climate challenges on human existence and progress. China's emissions in 2023 totaled 12.6 gigatons, representing 35% of global emissions, establishing it as the top carbon emitter globally. Combined with China's industrial structure, it is essential to investigate carbon reduction in the building sector due to its significant contribution to carbon emissions. This study introduces a third-party organization into the relationship between stakeholders, based on traditional government regulation. It constructs a three-party dynamic evolution model involving the government, environmental protection organization, and construction enterprise. The study analyzes the evolution process of the three-party strategy selection using evolutionary game theory. We analyze the elements influencing decision-making for the three parties through simulation analysis and provide appropriate recommendations. The study's findings indicate that low-carbon construction in China's construction sector is an intricate system involving several stakeholders, each guided by their own interests when determining their behavioral methods. Government penalties and financial subsidies can influence construction enterprises to adopt low-carbon production practices to some degree, but excessive rewards and punishments may not support system stability. [ABSTRACT FROM AUTHOR]

In this research, we investigate the horse racing game, a two-player game with six strategies. Our objective is to develop a theoretical framework for the game by employing the process of quantization. The Nash equilibrium (NE) of the quantum horse racing game is analyzed through an examination of the payoff matrix, and the results are compared to those of the classical horse racing game. Our findings demonstrate that the quantum horse racing game features both pure and mixed strategy NE, whereas the classical horse racing game possesses only mixed strategy NE. Additionally, our results indicate that the quantum horse racing game can mitigate the risks associated with the zero-sum game while outperforming the classical game. [ABSTRACT FROM AUTHOR]

The paper deals with the problem of securing a guaranteed victory for our side in the course of military operations, when the dynamic power of the enemy is known. The problem of the set of weapons for a guaranteed victory is solved. A method is given for calculating the set of weapons and equipment that guarantees victory without regard to information on the set of weapons and equipment of the opposing side for any set. The method of composing and solving matrix games in game theory is used. The problem is modeled as a matrix game with mixed strategies, and the existence of its solution (saddle point) is shown in this setting. To obtain a numerical solution of the problem, the matrix game is reduced to the linear programming problem.

A generalization of mixed strategy equilibrium is proposed, where mixed strategies need only be finitely additive and payoff functions are not required to be integrable or bounded. This notion of best-response equilibrium is based on an extension of the idea that an equilibrium strategy is supported in the player's set of best-response actions, but is applicable also when no best-response actions exist. It yields simple, natural equilibria in a number of well-known games where other kinds of mixed equilibrium are complicated, not compelling or do not exist. [ABSTRACT FROM AUTHOR]

We address a problem of preventing an interdiction on water supply networks by building a Bayesian Stackelberg game model involving stakeholders of a defender and an interdictor. The defender initiates to allocate resource to network components to make a trade-off between network resilience measured by water satisfaction rate and the defender's cost, whereas the interdictor follows to interdict a component with the objectives of maximising the destruction level on the network structure and minimising the interdictor's cost. Specifically, the defender adopts mixed defence strategies, which implies that the interdictor is uncertain of the defender's resource allocation. Moreover, we propose sufficient conditions for the elimination of the dominated defence and interdiction strategies. A decomposed iterative learning algorithm (DILA) and a smallest-depth binary-partition based hierarchical algorithm (SBHA) are developed to reduce the sizes of the defence and interdiction strategy sets, respectively, thus analysing the optimal mixed defence strategies. Finally, a real case study with private information is conducted, thus providing valuable suggestions for the defender's resource allocation against interdictions. [ABSTRACT FROM AUTHOR]

The discrete strategy game, in which agents can only choose cooperation or defection, has received lots of attention. However, this hypothesis seems implausible in the real world, where choices may be continuous or mixed. Furthermore, when applying Q -learning to continuous or mixed strategy games, one of the challenges is that the learning space grows drastically as the number of states and actions rises. So, in this article, we redesign the Q -learning method by considering the spatial reciprocity, in which agents simply interact with their four neighbours to get the reward and learn the action by taking neighbours' strategy into account. As a result, the learning state and action space is transformed into a 5×5 table that stores the state and action of the focal agent and its four neighbours, avoiding the curse of dimensionality caused by a continuous or mixed strategy game. The numerical simulation results reveal the striking differences between the three classes of games. In detail, the discrete strategy game is more vulnerable to the setting of relevant parameters, whereas the other two strategy games are relatively stable. At the same time, in terms of promoting cooperation, a mixed strategy game is always better than a continuous one. [ABSTRACT FROM AUTHOR]

Industrialization and increased energy use are leading to a greater influence of environmental and climate challenges on human existence and progress. China’s emissions in 2023 totaled 12.6 gigatons, representing 35% of global emissions, establishing it as the top carbon emitter globally. Combined with China’s industrial structure, it is essential to investigate carbon reduction in the building sector due to its significant contribution to carbon emissions. This study introduces a third-party organization into the relationship between stakeholders, based on traditional government regulation. It constructs a three-party dynamic evolution model involving the government, environmental protection organization, and construction enterprise. The study analyzes the evolution process of the three-party strategy selection using evolutionary game theory. We analyze the elements influencing decision-making for the three parties through simulation analysis and provide appropriate recommendations. The study’s findings indicate that low-carbon construction in China’s construction sector is an intricate system involving several stakeholders, each guided by their own interests when determining their behavioral methods. Government penalties and financial subsidies can influence construction enterprises to adopt low-carbon production practices to some degree, but excessive rewards and punishments may not support system stability.

Copyright of Journal of National University of Defense Technology / Guofang Keji Daxue Xuebao is the property of NUDT Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

For a discrete-time superreplication problem, a guaranteed deterministic formulation is considered: the problem is to ensure the cheapest coverage of the contingent claim on an option under all scenarios that are set using a priori defined compacts depending on the price history. Price increments at each moment of time must lie in the corresponding compact sets. We consider a market with trading constraints and no transaction costs. The statement of the problem is game-theoretic in nature and leads directly to the Bellman–Isaacs equations. In this article, we introduce a mixed extension of the "market" pure strategies. Several results concerning game equilibrium are obtained. [ABSTRACT FROM AUTHOR]

The positive impact of cooperative bots on cooperation within evolutionary game theory is well-documented. However, prior studies predominantly use discrete strategic frameworks with deterministic actions. This article explores continuous and mixed strategic approaches. Continuous strategies use intermediate probabilities for varying degrees of cooperation and focus on expected payoffs, while mixed strategies calculate immediate payoffs from actions taken within these probabilities. Using the prisoner's dilemma game, this study examines the effects of cooperative bots on human cooperation in both well-mixed and structured populations across these strategic approaches. Our findings reveal that cooperative bots significantly enhance cooperation in both population types under weak imitation scenarios, where players are less concerned with material gains. Conversely, under strong imitation scenarios, cooperative bots do not alter the defective equilibrium in well-mixed populations but have varied impacts in structured populations. Specifically, they disrupt cooperation under discrete and continuous strategies but facilitate it under mixed strategies. These results highlight the nuanced effects of cooperative bots within different strategic frameworks and underscore the need for careful deployment, as their effectiveness is highly sensitive to how humans update their actions and their chosen strategic approach.

The mixed redundancy strategy is one of the most powerful techniques for improving system performance. This novel strategy has, however, been mostly studied in non‐repairable redundant systems, while the present study aims to study, for the first time, its application to a repairable system with a repairman in availability and maintainability perspectives. In this system, a repairman is responsible for providing the repair services. The intended system simultaneously benefits from the repairman's vacation concept following different policies, namely: vacation interruption and multiple vacations. Moreover, the system consists of two types of repairs, specifically: regular and working vacation repair. Also, successive vacation times are governed by the Markovian arrival process. Accordingly, the system is analyzed by modeling a vector‐valued Markov process and several performance measures are derived in both transient and stationary regimes following the matrix‐analytic procedure. Finally, the performance of the proposed approach is verified using numerical examples that involve a system with three repairable non‐identical components under the mixed strategy as well as a micro‐grid system with three parallel subsystems as a real‐life case study. [ABSTRACT FROM AUTHOR]

We consider a guaranteed deterministic problem setting of discrete-time superreplication: the aim of hedging of a contingent claim is to ensure the coverage of possible payout under the option contract for all admissible scenarios. These scenarios are given by means of a priori given compact sets that depend on the prehistory of prices: the increments of the price at each moment of time must lie in the corresponding compact sets. The absence of transaction costs is assumed. The game-theoretic interpretation implies that the corresponding Bellman–Isaacs equations hold both for pure and mixed strategies. In the present paper, we propose a two-step method for solving the Bellman equation arising in the case of a (game) equilibrium. In particular, the most unfavorable strategies of the "market" can be found in the class of distributions concentrated at most at points, where is the number of risky assets. [ABSTRACT FROM AUTHOR]

Every player is expected to contribute to team's batting effort irrespective of their batting position. The expected contribution of each batsman is to score runs as quickly as possible without getting dismissed. It has often seen that based on different situations within a game, a batsman must play either carefully to defend his wicket or strike out aggressively to score runs quickly. Based on the expertise of the batsman, the captain of the fielding team arrange the fielders in such a way that the batsman couldn't maximize his score. However, the arrangement of fielders is also dependent on the type of bowler (spin/fast) as well as team's bowling strategies. Therefore, this study tries to find out the optimal playing strategies of a batsman on the field against different bowling types through the approach of game theory. To substantiate the model with live data a batsman's strategies against different types of bowlers are explained in this work. [ABSTRACT FROM AUTHOR]

Power infrastructure networks continue to be at risk under natural and anthropogenic hazard events. Cyberattacks targeting power grids aim at magnifying the impacts through damage propagation to other dependent infrastructure network. In this respect, the current study focuses on the "draw-down" phase of power infrastructure network resilience considering different centrality measures to evaluate the robustness of power grids against cyberattacks. The study considers two network representations for the grid based on the network's topological/connectivity (i.e., unweighted network) and the network's power flow data (i.e., weighted network). Therefore, the study utilizes the evaluated measures to improve network robustness under cyberattacks, through considering (or not) the proposed mixed strategy. Based on the analyses, network-level vulnerability is quantified considering five different scenarios through evaluating two key performance metrics—Topology and Functionality indices. Nonetheless, applying the proposed mixed strategy to limit the attacker's access to the network hubs would boost the overall grid robustness. [ABSTRACT FROM AUTHOR]

Summary: Recent advancements in the automotive area have aided in the development of smart vehicles with high processing, computing, and storage capabilities. These resources are leveraged to cope with the demands of consumer vehicles such as data analysis, optimization, and decision‐making. The first and foremost step in establishing this paradigm of computing so‐called vehicular cloud is the service selection. Nonetheless, vehicles' high mobility and the network's rapidly changing topology have addressed new challenges such as instability of resources, making their management complicated. Therefore, the vehicular cloud requires robust and efficient resource management solutions to be developed. In this article, we present a game theory‐based framework for vehicular resource selection where provider vehicles and consumer vehicles play a game against each other until reach equilibrium in order to enable consumer vehicles to select the most suitable provider vehicles that meet their requirements in terms of service quality and cost. Furthermore, a thorough study was carried out in order to study the interaction between players and predict their future behaviors. As this interaction will result in a pure and mixed equilibrium state, the convergence of the proposed theoretic model for both equilibrium states is rigorously demonstrated under certain assumptions. Effective search algorithms based on the best responses are designed to compute the pure and mixed Nash equilibrium. The suggested approach's verification is evaluated based on the satisfaction of the players and has shown better performance comparing previous algorithms. [ABSTRACT FROM AUTHOR]

One of the common approaches for improving the reliability of a specific system is to use parallel redundant components in subsystems. This approach, which is known as the redundancy allocation problem (RAP), includes the simultaneous selection of the component type and its level for each subsystem in order to maximize the system reliability.Traditionally, there are two redundancy strategies, namely active and standby, for the redundant components. Recently, a new powerful strategy called mixed strategy has been developed. It has been proved that the mixed strategy has a better performance when compared to both previous strategies. The main issue in utilizing the mixed strategy is its complicated formulation and sophisticated calculations, leading to a time-consuming procedure for solving the problems. Hence, in this paper, a new formulation based on the recursive approach is introduced to ease the calculation of the mixed strategy. In the new formulation, the complex double integral calculations are removed and the calculation times is reduced. The proposed recursive formulation provides a general statement for the mixed strategy formula which is not changed by altering the number of components in each subsystem. This flexibility and stability in the formula can be very important, especially for large scale cases. In order to evaluate the new approach and to compare its performances with the previous formulation, a benchmark problem with 14 subsystems is considered and the results of the two formulation are compared with each other.

The redundancy allocation problem (RAP) is an intriguing area in the field of reliability optimization to which a lot of research has been devoted in recent years. In this paper, a bi-objective model is developed for RAP with a heterogeneous backup scheme and a mixed redundancy strategy. Elimination of the lower bound estimation and the exact calculation of the reliability of the mixed strategy forms one of the most striking features of the proposed model. Investigating the optimal sequence of components in each subsystem, the study modifies a non-dominated sorting genetic algorithm (NSGA-II), as a powerful multi-objective evolutionary one, to solve the proposed bi-objective model. Two numerical examples will then be used to verify the efficiency of the model in achieving enhanced system reliability. Finally, the results of Pareto optimal set are used to demonstrate that the assumptions made enable the proposed model to improve system reliability by offering various structures while simultaneously considering system limitations. [ABSTRACT FROM AUTHOR]

The evolution of human cooperation is an important issue concerning social science. A deep understanding of human bounded rationality is a prerequisite for promoting collective cooperation and solving social dilemmas. Here we construct an asymmetric micro-dynamic based on bounded rationality from a micro perspective by combining behavioral economics and cognitive psychology with evolutionary game theory. Asynchronously updated Monte Carlo simulations were conducted where individuals were located on a square lattice to play a voluntary public goods game. The results showed that "free riding" behaviors can be effectively suppressed in most situations. The cooperation level can be obviously enhanced in a population comprising easily satisfied cooperators and greedy defectors. Moreover, essential conditions for the stability of the system are further discussed at the microscopic level, and altruistic behavior can be explained that an individual with lower expectations for or underestimation of a single game is more likely to cooperate. We argue that, compared to traditional approaches, the integration of interdisciplinary ideas should be taken more seriously. [ABSTRACT FROM AUTHOR]

We study the foundations for the development of optimal randomization in mixed strategy games. We consider a population of children and adolescents (7 to 16 years old) and study in the laboratory their behavior in a nonzero sum, hide‐and‐seek game with a unique interior mixed strategy equilibrium where each location has a known but different value. The vast majority of participants favor the high‐value location not only as seekers (as predicted by theory) but also as hiders (in contradiction with theory). The behavior is extremely similar across all ages, and also similar to that of the college students control adult group. We also study the use of cheap talk (potentially deceptive) messages in this game. Hiders are excessively truthful in the messages they send while seekers have a slight tendency to (correctly) believe hiders. In general, however, messages have a small impact on outcomes. The results point to a powerful (erroneous) heuristic thinking in two‐person randomization settings that does not get corrected, even partially, with age. [ABSTRACT FROM AUTHOR]

Price promotions and countercyclical pricing are driven by consumer search. This explanation is tested using a dynamic, structural, and seasonal inventory model. Previous studies have found that increases in price promotions lead decreases in the average price of seasonal goods in high-demand seasons, countering basic supply and demand predictions. I explain this phenomenon by proposing that price-sensitive consumers are less likely to search in low-demand periods, changing consumer composition and decreasing aggregate price elasticity. Simultaneously, consumer searches allow the firm to use price promotions to attract price-sensitive consumers while maintaining high average prices. I test this and other explanations using a seasonal dynamic structural inventory model where consumers make decisions on whether to search, which reveals price promotions and allows consumers to purchase. I find that price-sensitive consumers make up 14.9% of searching consumers in the low-demand season versus 29% in the high-demand season, resulting in increased price elasticity. The results suggest that consumer composition is changing due to the different search incentives of different segments. [ABSTRACT FROM AUTHOR]

Rational secure two-party computation is one of the important researches in cryptography. Since the purpose of rational parties is to maximize their own utilities, the parties prefer to use a mixed strategy, which will cause a change in entropy. Some protocols solved the problems of fairness and security by using entropy function and utility function respectively. However, the cost of ensuring protocol security by setting a really high utility function is often higher than the value of the protocol itself, and the protocol is only suitable for a single privacy requirement. In this paper, we propose a secure two-party computation protocol based on entropic criterion and set the corresponding security entropic threshold according to different privacy requirements. Secure entropy is used as a method to evaluate the security of two parties in different scenes. Furthermore, we explore the relationship between secure entropy and utility function, then to select the optimal utility function within the range of secure entropic threshold. The model we proposed is more flexible and universal. Furthermore, the security state of the model is well predicted. [ABSTRACT FROM AUTHOR]

4G is now deployed all over the world, but requirements are about to change rapidly face to the exponential growth on devices number, local service applications and spectrum scarce. To deal with that, 5G networks integrated Device To Device (D2D) communication as a key technology in its evolving architecture. From 3GPP Rel-12 to Rel-16, D2D succeeded to improve network capacity by enhancing spectrum reuse, data rates and reducing end-to-end latency. However, despite all these advantages, it implies new challenges in 5G system design as interference, spectrum and energy consumption. As a contribution, we propose in this paper a joint spectrum and energy efficient resource allocation algorithm for D2D communications. This approach maximizes the total spectrum efficiency and reduces UEs power consumption. Contrarily to most of previous studies on resource allocation problems considering only centralized and pure strategies approaches, we propose a distributed algorithm based on new mathematical game theory model as an interpretation of mixed strategy non cooperative game. We extend our previous research, by focusing on power consumption issue. Our proposed solution enhances joint SE/EE tradeoff by minimizing interferences and power consumption via a smart RB allocation. This new approach allows users to adopt more accurate strategies and maximize their utilities according to the random network behavior.

Maximizing overall system reliability by identifying optimal system configuration considering several design constraints is known as reliability redundancy allocation problem (RRAP). Since reliability is an important quality attribute in critical systems, RRAP has been intensively investigated in the literature. In this paper, a new model of RRAP for heterogeneous and homogeneous components is developed. Our proposed model handles component mixing in subsystems under both active and cold-standby redundancy strategies. The problem, therefore, is to decide the number of components in each subsystem (redundancy level), the failure rate of selected components, and the type of redundancy strategy for each of them under multiple design constraints including system weight, cost, and volume. Since RRAP falls into the NP-hard category of engineering optimization problems, a teaching learning-based optimization (TLBO) algorithm is implemented to solve it. Finally, the simulation results of the proposed RRAP model by TLBO on three well-known benchmark problems are provided, followed by the comparisons with recent existing related works. The comparative results suggested the effectiveness of the proposed approach in finding the optimal system configuration with higher system reliability in all cases. [ABSTRACT FROM AUTHOR]

We consider matrix games with two phenotypes (players): one following a mixed evolutionarily stable strategy and another one that always plays a best reply against the action played by its opponent in the previous round (best reply player, BR). We focus on iterated games and well-mixed games with repetition (that is, the mean number of repetitions is positive, but not infinite). In both interaction schemes, there are conditions on the payoff matrix guaranteeing that the best reply player can replace the mixed ESS player. This is possible because best reply players in pairs, individually following their own selfish strategies, develop cycles where the bigger payoff can compensate their disadvantage compared with the ESS players. Well-mixed interaction is one of the basic assumptions of classical evolutionary matrix game theory. However, if the players repeat the game with certain probability, then they can react to their opponents’ behavior. Our main result is that the classical mixed ESS loses its general stability in the well-mixed population games with repetition in the sense that it can happen to be overrun by the BR player. [ABSTRACT FROM AUTHOR]

Copyright of Al Bashaer Economic Journal is the property of Al Bashaer Economic Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Mixed strategy equilibria — Nash (NE) and maximin (MM) — are cornerstones of game theory, but their empirical relevance has always been questionable. We study in the laboratory two games, each with a unique NE and a unique (and distinct) MM in completely mixed strategies. Treatment variables include the matching protocol (pairwise random vs population mean matching), whether time is discrete or continuous, and whether players can specify explicit mixtures or only pure strategy realizations. NE mixes predict observed behavior relatively well in population mean matching treatments, and predict better than MM in all treatments. However, in most random pairwise treatments, uniform mixes predict better than NE. Regret-based and sign preserving dynamics capture regularities across all treatments. [ABSTRACT FROM AUTHOR]

The article examines the behavior of students and employers as a bimatrix game. With the tools of game theory, it is generally proven that the optimal strategy for employers is to pay low wages, and for students – not to study or to study too little. These two strategies form the Nash’s equilibrium in pure strategies. No specific numbers were used in the evidence, but only plausible assumptions about the relationships between the used parameters. This generalizes the conclusions made in the general case of higher education. [ABSTRACT FROM AUTHOR]

This research studies a resource pool-choice dilemma, in which a group of resource seekers independently choose between a larger pool containing more resources and a smaller pool containing fewer resources, knowing that the resources in each pool will be divided equally among its choosers, so that the more (fewer) people choose a certain pool, the fewer (more) resources each of them will get. This setting corresponds to many real-world situations, ranging from students choosing majors as a function of job opportunities to entrepreneurs choosing markets as a function of customer bases. Ten studies reveal a systematic undershooting bias: fewer people choose the larger pool relative to both the normative equilibrium benchmark and chance (random choice), thus advantaging those who choose the larger pool and disadvantaging those who choose the smaller pool. We present evidence showing that the undershooting bias is driven by bounded rationality in strategic thinking and discuss the relationship between our paradigm and other coordination games. This paper was accepted by Yuval Rottenstreich, decision analysis. [ABSTRACT FROM AUTHOR]

The latest maritime sulphur regulation poses a great challenge to effective enforcement issues. This study aims to achieve greater enforceability by proposing a novel self-reporting scheme, in which truthful reporting of non-compliance from the ship operator is certainly penalized with a smaller and ex-ante fine while falsified reporting of compliance is probabilistically penalized with a larger and ex-post fine as it has to be verified by the agency through random inspection. A simultaneous compliance game model is developed for the current enforcement scheme without self-reporting while a sequential game model is dedicated to self-reporting. Mixed strategy Nash equilibriums are derived separately to characterize the interactions between the agency's inspection strategy and ship operators' reporting strategy as well as complying strategy. Compared with the current scheme, it is demonstrated that self-reporting can always save some inspection costs as long as the current fine is between the smaller fine and the larger fine as specified in self-reporting. The savings come from the fact that the agency does not need to inspect some non-complying ship operators who report non-compliance. Moreover, the larger fine of falsified reporting acts as a stronger deterrent so that the inspection frequency can be decreased. In terms of total environmental cost (TEC) and total compliance cost (TCC), they cannot be decreased simultaneously. However, the total compliance rate can be improved together with TEC or TCC under certain conditions. Finally, self-reporting might decrease the total system cost without increasing the (total) penalty burdens perceived by (all) individual ship operators. The associated conditions are derived separately, allowing the policymakers to fine-tune the fine levels so that self-reporting can replace the current enforcement scheme and satisfy certain policy targets with higher acceptability from the stakeholders. [ABSTRACT FROM AUTHOR]

We modify a canonical participation game used to study International Environmental Agreements (IEA), considering both mixed and pure strategies at the participation stage, and including a prior cost-reducing investment stage. The use of mixed strategies at the participation stage reverses a familiar result and alsoreverses the policy implication of that result: with mixed strategies, equilibriumparticipation and welfare is higher in equilibria that involve higher investment.