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We investigate a robust equilibrium investment-reinsurance problem for n ambiguity-averse competitive insurers, n ≥ 2 . Each insurer is allowed to purchase proportional reinsurance and invest in a risk-free asset and a risky asset. Each insurer aims to maximize the expected utility of a weighted relative terminal wealth with respect to the other competitors. In this article, the risky asset is assumed to follow a general and flexible model: the square root factor process. Following the game theory approach, we derive the closed solutions of the robust equilibrium investment-reinsurance strategies. Moreover, the verification theorem is provided in this article. Finally, we demonstrate some numerical analyses and give the economic explanations as well. [ABSTRACT FROM AUTHOR]

This article provides an overview of utility functions and expected utility theory in economic decision-making. It discusses the history of expected utility theory, including the St. Petersburg paradox and the development of prospect theory as an alternative. The article also explores the concept of utility saturation and its impact on risk aversion. It introduces the use of Markov chains to analyze decision-making and concludes by acknowledging the limitations of models in understanding expected utility theory. [Extracted from the article]

We consider a distributed computing setting wherein a central entity seeks power from computational providers by offering a certain reward in return. The computational providers are classified into long-term stakeholders that invest a constant amount of power over time and players that can strategize on their computational investment. In this paper, we model and analyze a stochastic game in such a distributed computing setting, wherein players arrive and depart over time. While our model is formulated with a focus on volunteer computing, it equally applies to certain other distributed computing applications such as mining in blockchain. We prove that, in Markov perfect equilibrium, only players with cost parameters in a relatively low range which collectively satisfy a certain constraint in a given state, invest. We infer that players need not have knowledge about the system state and other players' parameters, if the total power that is being received by the central entity is communicated to the players as part of the system's protocol. If players are homogeneous and the system consists of a reasonably large number of players, we observe that the total power received by the central entity is proportional to the offered reward and does not vary significantly despite the players' arrivals and departures, thus resulting in a robust and reliable system. We then study by way of simulations and mean field approximation, how the players' utilities are influenced by their arrival and departure rates as well as the system parameters such as the reward's amount and dispensing rate. We observe that the players' expected utilities are maximized when their arrival and departure rates are such that the average number of players present in the system is typically between 1 and 2, since this leads to the system being in the condition of least competition with high probability. Further, their expected utilities increase almost linearly with the offered reward and converge to a constant value with respect to its dispensing rate. We conclude by studying a Stackelberg game, where the central entity decides the amount of reward to offer, and the computational providers decide how much power to invest based on the offered reward. [ABSTRACT FROM AUTHOR]

The implications and contagion effect of emotion cannot be ignored in rumor spreading. This paper sheds light on how decision makers' (DMs) emotion type and intensity affect rumor spreading. Based on the rank-dependent expected utility (RDEU) and evolutionary game theory (EGT), we construct an evolutionary game model between rumormongers (RMs) and managers (Ms) by considering emotions. We use MATLAB to simulate and reveal the influencing mechanism of DMs' emotion type and intensity on rumor spreading. The results indicate that the DMs' strategy choice is not only affected by their own emotion preference and intensity, but also by the other players in rumor spreading. Moreover, pessimism has a more significant influence than optimism on the stability of the evolutionary game, Ms' emotion is more sensitive to the game results than RMs' emotion and the emotion intensity is proportional to the evolution speed. More significantly, some earthshaking emotional thresholds are found, which can be used to predict RMs' behavior, help Ms gain critical time to deal with rumors, and avoid the Tacitus Trap crisis. Furthermore, the evolution results fall into five categories: risk, opportunity, ideal, security and hostility. The results of this work can benefit Ms' public governance. [ABSTRACT FROM AUTHOR]

In view of the random retail price and retailer's preference for retail price risk aversion, we used mean-variance to describe the uncertainty risk of retail price. To study the impacts of both the retail price uncertainty risk and retail price risk aversion preference on supply chain (SC) decision-making, we constructed a SC game model based on three different power structures, including Manufacturer Stackelberg (MS) game, Retailer Stackelberg (RS) game, and Vertical Nash (VN) game. The results showed that the retail price uncertainty risk and the retailer's retail price risk aversion preference weakened the manufacturer's production effort input, decreased the retailer's enthusiasm for ordering, and damaged the interests of manufacturer and retailer. Under the three different power structures, the production effort input of the manufacturer depended on the production effort affecting wholesale price efficiency and retail price efficiency. The retailer's expected utility was largest under the MS game model and smallest under the VN game model. The manufacturer's profits were closely related to each parameter under the three respective power structures. This study provides theoretical guidance for the decision-making of SC enterprises with retail price risk and retailer with retail price risk aversion preference under different power structure situations. [ABSTRACT FROM AUTHOR]

We study a cyber security game between a defender who wishes to defend her information assets and an attacker who tries to attack them. In this game the attacker and the defender choose how to distribute their resources in attacking or defending the different information assets. Given these investments the probability that an attack on a given asset is successful is an increasing function of the attacker's investment and a decreasing function of the defender's investment. The defender tries to minimize the expected damage from the attacks plus the cost of the defense while the attacker tries to maximize the expected damage from attacks minus his attacks' expenses. The attacker is constrained by a budget. We compare two scenarios: a sequential move game and a simultaneous game. In the sequential game the defender moves first by deciding how much resources to allocate to the defense of each information asset and the attacker observes these investments and responds by allocating his resources in a manner that maximizes his expected utility. In the simultaneous game the attacker does not observe the defender's decision before making his own. We analyze the best response strategies of the players and the equilibria of each of these games. Based on this analysis, we provide a tight upper bound on the reduction in defender's costs that can be achieved by moving from the simultaneous to the sequential game. [ABSTRACT FROM AUTHOR]

In this paper, we consider the optimal reinsurance problem for a risk model with a thinning-dependence structure, where the stochastic sources related to claim occurrence are classified into different groups, and each group may cause a claim in each insurance class with some probability. We assume that the insurer can manage the risk by purchasing per-loss reinsurance, and their aim is to maximize the expected utility of the terminal wealth. By using the technique of stochastic control, we obtain the corresponding Hamilton–Jaccobi–Bellman equation. From the perspective of game theory, we derive the closed-form expression of the optimal strategy for each class of business, which is actually the best response to other given strategies. We also investigate the necessary conditions for optimal strategies and transfer the original optimization problem into a system of equations. Furthermore, we prove that the solution of the system of equations always exists, but may not be unique, and we also study some features of the optimal strategies in special cases and derive several interesting results. Finally, some numerical examples are given to show the impacts of some important parameters on the optimal strategies. [ABSTRACT FROM AUTHOR]

In this paper we use the repeated-games framework to design and analyze a master-worker (MW) mechanism, where a master repeatedly outsources computational tasks to workers in exchange for payment. Previous work on MW models assumes that all workers are perfectly rational and aim to maximize their expected utility. Perfect rationality is a strong behavioral assumption because it requires that all workers follow the prescribed equilibrium. Such a model may be unrealistic in a practical setting, where some agents are not perfectly rational and may deviate from the equilibrium for short-term gains. Since the correctness of these MW protocols relies on workers following the equilibrium strategies, they are not robust against such deviations. We augment the game-theoretical MW model with the presence of such bounded-rational players or deviators. In particular, we show how to design a repeated-games based MW Verifiable Crowd Computing mechanism that incentivizes the rational workers (or followers) to effectively punish such deviators through the use of terminal payments. We show that the master can use terminal payments to obtain correct answers to computational problems even in this more general model. We supplement our theoretical results with simulations that show that our mechanism outperforms related approaches. [ABSTRACT FROM AUTHOR]

This paper studies games when agents have second-order expected utility. It examines the theoretical predictions of the model and compares its performance in explaining behavior in experimental data on games with that of quantal response equilibrium. [ABSTRACT FROM AUTHOR]

We consider a game on a graph G = ⟨ V , E ⟩ with two confronting classes of randomized players: ν attackers, who choose vertices and seek to minimize the probability of getting caught, and a single defender, who chooses edges and seeks to maximize the expected number of attackers it catches. In a Nash equilibrium, no player has an incentive to unilaterally deviate from her randomized strategy. The Price of Defense is the worst-case ratio, over all Nash equilibria, of ν over the expected utility of the defender at a Nash equilibrium. We orchestrate a strong interplay of arguments from Game Theory and Graph Theory to obtain both general and specific results in the considered setting: (1) Via a reduction to a Two-Players, Constant-Sum game, we observe that an arbitrary Nash equilibrium is computable in polynomial time. Further, we prove a general lower bound of | V | 2 on the Price of Defense. We derive a characterization of graphs with a Nash equilibrium attaining this lower bound, which reveals a promising connection to Fractional Graph Theory; thereby, it implies an efficient recognition algorithm for such Defense-Optimal graphs. (2) We study some specific classes of Nash equilibria, both for their computational complexity and for their incurred Price of Defense. The classes are defined by imposing structure on the players' randomized strategies: either graph-theoretic structure on the supports, or symmetry and uniformity structure on the probabilities. We develop novel graph-theoretic techniques to derive trade-offs between computational complexity and the Price of Defense for these classes. Some of the techniques touch upon classical milestones of Graph Theory; for example, we derive the first game-theoretic characterization of König-Egerváry graphs as graphs admitting a Matching Nash equilibrium. [ABSTRACT FROM AUTHOR]

We characterize lexicographic conditional probability systems (LCPSs). Our aim is to address an issue left open in an important contribution by Blume et al. (1991a). They provide a characterization of LCPSs, but one of their axioms quite explicitly imposes disjointness of the supports in an LCPS. The main new axiom is robustness, which is a weak continuity requirement on preferences. It requires preferences between acts x and y to be robust to (unchanged by) small perturbations in payoffs x ω and y ω for some state ω where x and y are different. LCPSs are characterized as the subclass of lexicographic probability systems satisfying robustness. As a corollary we provide an axiomatization of LCPSs in terms of standard properties satisfied by subjective expected utility preferences (as in Anscombe and Aumann (1963)) and robustness. [ABSTRACT FROM AUTHOR]

The centipede game posits one of the most well‐known paradoxes of backward induction in the literature of experimental game theory. Given that deviations from the unique subgame perfect Nash equilibrium generates a Pareto improvement, several theoretical models have been employed in order to rationalize this kind of behavior in this social dilemma. The available explanations range from social preferences including fairness, altruism or cooperation motives, errors in playing, inability to perform backward induction or different depths of reasoning. In the present study, we use the Blavatskyy's theoretical contribution, and relax the assumptions of Expected Utility maximization and risk‐neutral attitudes, to test an alternative explanation. We compare various probabilistic decision theory models in terms of their descriptive (in‐sample) and predictive (out‐of‐sample fit) performance, using data from experimental centipede games. We find that introducing non‐Expected Utility preferences to the Quantal Response Equilibrium model, along with a nonlinear utility function, provides a better explanation compared to alternative specifications such as the Level‐k or the Quantal Response Equilibrium model with altruistic motives. [ABSTRACT FROM AUTHOR]

• By analyzing the possible interaction going on between a transport company and a driver, the actors' efforts in production might be strategic complements or substitutes, implying that high effort from one of the actors could either induce high or low effort from the other. • High efforts from both the driver and the company would mean high accident risks. • An optimal pay contract is characterized by a pay for performance contract where the driver's share of net revenue becomes higher the higher influence a marginal increase in her effort has on the net revenue, the lower influence a marginal increase in her effort has on the probability of accidents, and the lower the loss the company experiences if an accident occurs. • When such a contract is used, the driver faces a situation where the transport company's interests are perfectly internalized, meaning that the company also maximizes the sum of the expected profit and utility. • However, since accidents also mean costs for others apart from the driver and the company, public regulation is needed to ensure overall welfare. We propose a theoretical model in order to study the behavior of a road transport company and a driver. The driver is supposed to face a pay for performance contract. The expected profit for the company and the expected utility for the driver depend on the input chosen by themselves and the other actor. By analyzing the possible interaction going on between the actors in a simultaneous game and the two possible leader-follower games, it is seen that the efforts could be strategic complements, independent or strategic substitutes. In cases where the efforts are strategic complements, and the expected profit for the company and the expected utility for the driver are increasing in the other actor's effort, leader-follower games trigger higher accident risks than the simultaneous game. If efforts are strategic complements, and the expected profit and utility are decreasing in the other actor's effort, leader-follower games produce lower accident risks than when the actors move simultaneously. Presuming that the transport company is the principal and the driver is the agent, we deduce an optimal pay contract. The optimal contract is characterized by a pay for performance contract where the driver's share of net revenue becomes higher the higher influence a marginal increase in her effort has on the net revenue, the lower influence a marginal increase in her effort has on the probability of accidents, and the lower the loss the company experiences if an accident occurs. When such a contract is used, the driver faces a situation where the transport company's interests are perfectly internalized, meaning that the company also maximizes the sum of the expected profit and utility. However, since accidents also mean costs for others apart from the driver and the company, public regulation is needed to ensure overall welfare. [ABSTRACT FROM AUTHOR]

Abundant evidence exists that expected utility theory does not adequately describe decision making under risk. Although prospect theory is a popular alternative, it is rarely applied in strategic situations in which risk arises through individual interactions. This study fills this research gap by incorporating prospect theory preferences into a dynamic game theoretic model. Using a large field data set from multiple online pay-per-bid auction sites, the authors empirically show that their proposed model with prospect theory preferences makes a better out-of-sample prediction than a corresponding expected utility model. Prospect theory also provides a unified explanation for two behavioral anomalies: average auctioneer revenues above current retail prices and the sunk cost fallacy. The empirical results indicate that bidders are loss averse and overweight small probabilities, such that the expected revenue of the auction exceeds the current retail price by 25.46%. The authors illustrate and empirically confirm a managerial implication for how an auctioneer can increase revenue by changing the details of the auction design. [ABSTRACT FROM AUTHOR]

We develop the expected utility function model of referring patients from a comprehensive hospital to a community healthcare centre using M/M/1 queueing and game theory in a hierarchical healthcare system. The equilibrium downstream referral rates and equilibrium utilities of hospitals are obtained. We find that the equilibrium downstream referral rates increase with the patients' preference for the comprehensive hospital. The lower the difference between partition criterion of two-stage treatment, the lower the equilibrium downstream referral rates, which benefits the hospital. When the motivation of the comprehensive hospital with patients referral is low, we can achieve all-win of the comprehensive hospital, the community healthcare centre and the whole healthcare system by a payment strategy. We use a numerical experiment to discuss the effect of payment on equilibrium downstream referral rates and equilibrium utilities, and compare the equilibrium downstream referral rates and equilibrium utilities in the payment strategy and the non-payment strategy cases, then give some management implications and provide some theoretical support and policy reference to promote effective implementation of referral. [ABSTRACT FROM AUTHOR]

Highlights • Auction-theory-based method is proposed for calculating coalition utility • Coalition formation techniques are introduced to find stable coalition partition • Economy benefits of microgrids cooperation are simulated and analyzed Abstract The future distribution network may encompass a large number of microgrids, in which case local networked microgrids can be formed and all the microgrids in the network be connected to the main grid through a distribution sub-station. To improve the efficiency of the entire network rather than focusing on improving the efficiency and reliability of each microgrid, this paper proposes a coalitional-game-theory-based local power exchange algorithm to identify incentives for coalitional operation and help microgrids in the network trade power locally with neighboring microgrids, so as to meet their own power requirements while achieving higher expected individual utility. Compared with the traditional operation situation, simulation results show that the proposed coalitional- game-theory-based local power exchange algorithm can help increase individual microgrid utility in the network. When there are 30 microgrids in the network, for example, each microgrid is expected to have a 16% increment of individual utility on average. [ABSTRACT FROM AUTHOR]

Some terrorist organizations provoke their targets into deploying massive countermeasures, allowing terrorists to mobilize a greater share of their audience. Why would a government pursue such a costly strategy if it only strengthens the opponent? I develop a signaling model of terrorism, counterterrorism, and recruitment. If a target government is unsure whether the terrorists' audience is sympathetic to the cause, weaker groups sometimes bluff strength by attacking. To check this bluff, governments sometimes respond to attacks with large-scale operations, even though they know they might be overreacting. Comparative statics reveal that overreaction regret is most likely when the target is wealthy and large operations are more effective. Thus, a selection effect creates the false impression that provocation is most effective against geopolitically privileged targets. [ABSTRACT FROM AUTHOR]

Bayesian game theorists claim to represent players as Bayes rational agents, maximising their expected utility given their beliefs about the choices of other players. I argue that this narrative is inconsistent with the formal structure of Bayesian game theory. This is because (i) the assumption of common belief in rationality is equivalent to equilibrium play, as in classical game theory, and (ii) the players' prior beliefs are a mere mathematical artefact and not actual beliefs held by the players. Bayesian game theory is thus a Bayesian representation of the choice of players who are committed to play equilibrium strategy profiles. [ABSTRACT FROM AUTHOR]

This paper studies n -player games where players' beliefs about their opponents' behavior are capacities (fuzzy measures, non-additive probabilities). The concept of an equilibrium under uncertainty was introduced by J. Dow and S. Werlang [5] for two players and was extended to n -player games by J. Eichberger and D. Kelsey [8] . Expected utility was expressed by Choquet integral. We consider the concept of an equilibrium under uncertainty in this paper but with expected utility expressed by Sugeno integral. Existence of such an equilibrium expressed by possibility (or necessity) capacities is demonstrated using some abstract non-linear convexity on the space of capacities. [ABSTRACT FROM AUTHOR]

This paper substitutes the standard rationality assumption with approximate rationality in normal form games. We assume that players believe that their opponents might be ε -rational, i.e. willing to settle for a suboptimal choice, and so give up an amount ε of expected utility, in response to the belief they hold. For every player i and every opponents’ degree of rationality ε , we require player i to attach at least probability F i ( ε ) to his opponent being ε -rational, where the functions F i are assumed to be common knowledge amongst the players. We refer to this event as belief in F -rationality. The notion of Common Belief in F -Rationality ( CB F R ) is then introduced as an approximate rationality counterpart of the established Common Belief in Rationality. Finally, a corresponding recursive procedure is designed that characterizes those beliefs players can hold under CB F R . [ABSTRACT FROM AUTHOR]

I study the implications of Wald's (1947) complete class theorem for decision making under Knightian uncertainty (or ambiguity). Suppose we call someone who uses Wald's approach to statistical decision making a Waldian. A Waldian may then have preferences over acts that are not in agreement with subjective expected utility but always chooses as if she was a subjective expected utility maximizer. In particular, even Wald's (1945) minmax decision rule is consistent with subjective expected utility. [ABSTRACT FROM AUTHOR]

In the Approval Bargaining game, two players bargain over a finite set of alternatives. To this end, each one simultaneously submits a utility function u jointly with a real number α ; by doing so she approves the lotteries whose expected utility according to u is at least α . The lottery to be implemented is randomly selected among the most approved ones. We first prove that there is an equilibrium where players truthfully reveal their utility function. We also show that, in any equilibrium, the equilibrium outcome is approved by both players. Finally, every equilibrium is sincere and Pareto efficient as long as both players are partially honest. [ABSTRACT FROM AUTHOR]

Purpose Among the many perspectives to analyze war, such as rational actor, organizational process, governmental politics and ethics, the perspective that actually incorporates the costs and benefits into a systematic theoretical structure has hardly been analyzed. The purpose of this paper is to analyze the costs and benefits perspective.Design/methodology/approach Three kinds of value are distinguished, i.e. human, economic and influence. Different actors (politicians, populations, stakeholders, etc). assign different weights to the three kinds of value. Six gradually more complicated models are developed. The first subtracts losses from gains for the three kinds of value. Thereafter, the paper accounts for multiple periods, time discounting, attitude towards risk, multiple stakeholders, subcategories for the three kinds of value, sequential decision-making and game theory.Findings The rich theoretical structure enables assessing costs and benefits more systematically and illuminatingly. The cost benefit analysis is illustrated with the 2003-2011 Iraq War. The paper estimates gained and lost value of human lives, economic value and influence value, and show how different weights impact the decision of whether to initiate war differently.Originality/value The paper provides scientists and policy makers with a theoretical structure within which to evaluate the costs and benefits of war, accounting for how different actors estimate weights, the future, risk and a variety of parameter values differently. [ABSTRACT FROM AUTHOR]

In game theory, there are two social interpretations of rewards (payoffs) for decision-making strategies: (1) the interpretation based on the utility criterion derived from expected utility theory and (2) the interpretation based on the quantitative criterion (amount of gain) derived from validity in the empirical context. A dynamic decision theory has recently been developed in which dynamic utility is a conditional (state) variable that is a function of the current wealth of a decision maker. We applied dynamic utility to the equal division in dove-dove contests in the hawk-dove game. Our results indicate that under the utility criterion, the half-share of utility becomes proportional to a player’s current wealth. Our results are consistent with studies of the sense of fairness in animals, which indicate that the quantitative criterion has greater validity than the utility criterion. We also find that traditional analyses of repeated games must be reevaluated. [ABSTRACT FROM AUTHOR]

Multiple autonomous agents interact over a random communication network to maximize their individual utility functions which depend on the actions of other agents. We consider decentralized best-response with inertia type algorithms in which agents form beliefs about the future actions of other players based on local information, and take actions that maximize their expected utilities computed with respect to these beliefs or continue to take their previous actions. We show convergence of these types of algorithms to a Nash equilibrium in weakly acyclic games. The result depends on the condition that the belief update and information exchange protocols successfully learn the actions of other players with positive probability in finite time given a static environment, i.e., when other agents' actions do not change. We design a decentralized fictitious play algorithm with voluntary and limited communication (DFP-VL) protocols that satisfy this condition. In the voluntary communication protocol, each agent decides whom to exchange information with by assessing the novelty of its information and the potential effect of its information on others' beliefs. The limited communication protocol entails agents sending only their most frequent action to agents that they decide to communicate with. Numerical experiments on a target assignment game demonstrate that the voluntary and limited communication protocol can more than halve the number of communication attempts while retaining the same convergence rate as DFP in which agents constantly attempt to communicate. [ABSTRACT FROM AUTHOR]

Strategic decision making in animal healthcare involves an array of complex factors interacting for the allocation of scarce resources. Consequently, modelling techniques which consider the actions and interactions of multiple decision makers, such as game theory and agency theory, have potential to provide insight of past and future interventions and policy which seek to improve economic efficiency. This scoping review aimed to identify, describe, and synthesise literature relating to multi-actor strategic decision making in animal healthcare. Embase, Web of Science, PubMed, CAB direct, EconLit, and AnthroSource were searched for literature published until November 2020. Studies were included if they were written in English, modelled strategic decisions between multiple actors, and contained information that related to animal healthcare practices. Data were analysed within the context of a conceptual framework based on strategic decision-making literature and modelling techniques. The identified literature (n = 31) had a strong focus on livestock healthcare and particularly on cattle (n = 13). Most studies (27/31) examined decisions concerning infectious disease and seven studies used compartmental models to include disease prevalence data. Almost all the articles (n = 30) used the monetary outcome of strategic decisions as a basis for expected utility, either through direct profit maximisation or via the aversion of losses. Nine studies used discursive and conceptual models to describe the strategic decision-making process, providing a wide lens by which to view decisions and opportunity to discuss the role of behavioural contributors to utility. Twenty-two studies used formal mathematical models to describe strategic decisions and used model solutions to provide recommendations to a specific problem, ten of which were parameterised with empirical data. Consequently, 20 articles provided specific policy recommendations to improve the welfare output of a system, the majority of which suggested the need for an increased level of state intervention in the animal health sector. This review describes the range of studies which have approached strategic decision making in animal healthcare through multi-player modelling techniques. These modelling techniques provide opportunity to consider the perspectives of multiple stakeholders and to combine economic and epidemiological data which may be beneficial to the development of animal health interventions. [ABSTRACT FROM AUTHOR]

We introduce asymmetric information to games with discontinuous payoffs and prove new equilibrium existence theorems. In particular, the seminal work of Reny (1999) is extended to a Bayesian preferences framework. [ABSTRACT FROM AUTHOR]

We develop awareness-dependent subjective expected utility by taking unawareness structures introduced in Heifetz et al. (J Econ Theory 130:78-94, ; Games Econ Behav 62:304-324, ; Unawareness, beliefs, and speculative trade. University of California, Davis, ) as primitives in the Anscombe-Aumann approach to subjective expected utility. We observe that a decision maker is unaware of an event if and only if her choices reveal that the event is 'null' and the negation of the event is 'null'. Moreover, we characterize 'impersonal' expected utility that is behaviorally indistinguishable from awareness-dependent subject expected utility and assigns probability zero to some subsets of states that are not necessarily events. We discuss in what sense probability zero can model unawareness. [ABSTRACT FROM AUTHOR]

Game theorists typically assume that changing a game's payoff levels--by adding the same constant to, or subtracting it from, all payoffs--should not affect behavior. Although this invariance is an implication of the theory when payoffs mirror expected utilities, it is an empirical question when "payoffs" are actually money amounts. Loss avoidance is a phenomenon where payoff-level changes matter when they change the signs of payoffs: gains become losses or vice versa. We report the results of a human-subjects experiment designed to test for two types of loss avoidance: certainloss avoidance (avoiding a strategy leading to a sure loss, in favor of an alternative that might lead to a gain) and possible-loss avoidance (avoiding a strategy leading to a possible loss, in favor of an alternative that leads to a sure gain). Subjects in the experiment play three versions of Stag Hunt, which are identical up to the level of payoffs, under a variety of treatments. We find strong evidence of behavior consistent with certain-loss avoidance in the experiment. We also find evidence of possible-loss avoidance, although weaker than that for certain-loss avoidance. Our results carry implications for theorists modeling real-life situations with game theory and for experimenters attempting to test theory and interpret observed behavior in terms of theory. [ABSTRACT FROM AUTHOR]

Abstract: Optimism bias is inconsistent with the independence of decision weights and payoffs found in models of choice under risk and uncertainty, such as expected utility theory, subjective expected utility, and prospect theory. We therefore propose an alternative model of risky and uncertain choice where decision weights—affective or perceived risk—are endogenous. Affective decision making (ADM) is a strategic model of choice under risk and uncertainty where we posit two cognitive processes—the “rational” and the “emotional” process. The two processes interact in a simultaneous-move intrapersonal potential game, and observed choice is the result of a pure strategy Nash equilibrium in this game. We show that regular ADM potential games have an odd number of locally unique pure strategy Nash equilibria, and demonstrate this finding for affective decision making in insurance markets. We prove that ADM potential games are refutable by axiomatizing the ADM potential maximizers. [Copyright &y& Elsevier]

Abstract: Neuroeconomics is a rapidly growing new research discipline aimed at describing the neural substrate of decision-making using incentivized decisions introduced in experimental economics. The novel combination of economic decision theory and neuroscience has the potential to better examine the interactions of social, psychological and neural factors with regard to motivational forces that may underlie psychiatric problems. Game theory will provide psychiatry with computationally principled measures of cognitive dysfunction. Given the relatively high heritability of these measures, they may contribute to improving phenotypic definitions of psychiatric conditions. The game-theoretical concepts of optimal behavior will allow description of psychopathology as deviation from optimal functioning. Neuroeconomists have successfully used normative or near-normative models to interpret the function of neurotransmitters; these models have the potential to significantly improve neurotransmitter theories of psychiatric disorders. This paper will review recent evidence from neuroeconomics and psychiatry in support of applying economic concepts such as risk/uncertainty preference, time preference and social preference to psychiatric research to improve diagnostic classification, prevention and therapy. [Copyright &y& Elsevier]

Abstract: We use a modified version of the dictator game to study whether perceived unfairness affects giving. To earn money, dictators first had to take a test. Our treatment group had participants taking tests of different difficulty levels while the control group had all participants taking a test of the same difficulty level. We found that participants who were in an environment where everyone faced the same challenge to earn money were less generous than participants in an environment where some people had an advantage while others had a disadvantage. [Copyright &y& Elsevier]

We consider the problem of expected utility maximization for the two-agent case in general semimartingale model. For this case a cooperative investment game is posed as follows: firstly collect both agents' capital as a whole at the initial time, and invest it in a trading strategy. Then at some time T0 one agent quits cooperation and terminates investment, so they divide the wealth and each of them gets a part. During the time interval [T0, T], the other agent invests her capital in a new trading strategy herself. By stochastic optimization methods with the help of the theory of backward stochastic differential equations, we give a characterization of Pareto optimal cooperative strategies and a characterization of situations where cooperation strictly Pareto dominates non-cooperation in our model. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents a new iterative procedure for solving finite non-cooperative games, the reasoning-based expected utility procedure (RBEU), and compares this with existing iterative procedures. RBEU deletes more strategies than iterated deletion of strictly dominated strategies, while avoiding the conceptual problems associated with iterated deletion of weakly dominated strategies. It uses a sequence of “accumulation” and “deletion” operations to categorise strategies as permissible and impermissible; strategies may remain uncategorised when the procedure halts. RBEU and related “categorisation procedures” can be interpreted as tracking successive steps in players'' own reasoning. [Copyright &y& Elsevier]

Abstract: The calibration theorem by Rabin [Rabin, M., 2000a. Risk aversion and expected utility theory: A calibration theorem. Econometrica 68, 1281–1292; Rabin, M., 2000b. Diminishing marginal utility of wealth cannot explain risk aversion. In: Kahneman, D., Tversky, A. (Eds.), Choices, Values and Frames. Cambridge University Press] implies that seemingly plausible small-stake choices under risk imply implausible large-stake risk aversion. This theorem is derived based on the expected utility of wealth model. However, Cox and Sadiraj [Cox, J.C., Sadiraj, V., 2006. Small- and large-stakes risk aversion: Implications of concavity calibration for decision theory. Games Econ. Behav. 56, 45–60] show that such implications do not follow from the expected utility of income model. One may then wonder about the implications for more applied consumption analysis. The present paper therefore expresses utility as a function of consumption in a standard life cycle model, and illustrates the implications of this model with experimental small- and intermediate-stake risk data from Holt and Laury [Holt, C.A., Laury, S.K., 2002. Risk aversion and incentive effects. Amer. Econ. Rev. 92, 1644–1655]. The results suggest implausible risk aversion parameters as well as unreasonable implications for long-term risky choices. Thus, the conventional intertemporal consumption model under risk appears to be inconsistent with the data. [Copyright &y& Elsevier]

Well-known conflict equilibria are used to formulate the concept of fair distribution, and a technique is proposed to find it in an arbitrary cooperative game. Any cooperative game is shown to have only one fair distribution, which can always be found from the formulas of conflict equilibrium theory. [ABSTRACT FROM AUTHOR]

• Closed-form solutions for determining the optimum maintenance intervals have been developed. • Expected Utility Theory (EUT) is applied to find the optimal results. • The presented technique have been designed based on Weibull and Exponential distributions. • Four different types of field instruments from a typical gas plant have been considered in this study. • Practical implementation of the methodology confirms its high efficiency, compared with the previous heuristic maintenance strategy. With the increasing demand for complicated control and monitoring systems in chemical process plants based on tremendous improvements in the digital world, the number of devices for monitoring and controlling the plants has risen dramatically. In such huge networks of a myriad of instrument devices, determination of an optimum proactive maintenance interval (PMI) has become vital for enhancing plant safety and reducing maintenance costs. PMI optimization is a matter of considerable benefit variation, process reliability, personnel safety, and environmental concerns. In this paper, a comprehensive formula and a concise formula are developed and applied for obtaining the optimum PMI based on the expected utility theory. The proposed formulas are applicable for determining the most affordable and effective maintenance plan providing the lowest cost and acceptable reliability, availability, and safety in oil and gas industries in terms of an optimal decision-making problem. By considering variable failure rates and components' wear and tear, a comprehensive formula has been developed. Moreover, for constant failure rate and returning to the "as-new" condition after each proactive maintenance, a concise and "easy-to-use" formula has been obtained. Finally, it has been shown through practical implementation of the presented methodology in a typical gas refinery that about 41% benefit is achieved in one year, compared with the previous heuristic maintenance strategy in the same duration. [ABSTRACT FROM AUTHOR]

• We study a sequential defender-attacker game; • Multiple strategies and targets are considered; • Learning and counter-learning behaviors are modeled; • The interaction between targets resulting in additional utility is allowed; • Comparative studies are implemented to see how parameters affect the equilibrium. Appropriate resource allocation among multiple targets plays a vital role in the defender-attacker game. Traditional methods seldom consider the optimal resource allocation with more than one strategy among multiple targets. Accordingly, we assume that the defender moves first, allocating resources in deploying different false targets and strengthening the genuine ones among multiple targets. The attacker moves after observing the defender's move, distributing resources in identifying false targets and then attacking the genuine ones concerning multiple targets. Each player aims to maximize their own overall expected utility given any of the other player's move. The optimal resource distribution between target intelligence/protection for the defender and target identification/attack efforts among multiple targets for the attacker is studied. We model and obtain analytical equilibrium results under various parameter settings. Our results show that increased intelligence (impact) contest intensities lead to lower (higher) attacker resources in intelligence (attack). Moreover, the zero-sum game where both players share the same preferences without additional payoff consideration results in the worst losses for the defender. The forgoing method offers an original way to approach the resource allocation problems in security defense fields. [ABSTRACT FROM AUTHOR]

Risk aversion in game theory is usually modeled using expected utility, which was criticized early on, leading to an extensive literature on generalized expected utility. In this paper we are the first to apply μ – σ theory to the analysis of (static) games. μ – σ theory is widely accepted in the finance literature; using it allows us to study the effect on uncertainty endogenous to the game, i.e., mixed equilibria. In particular, we look at the case of linear μ – σ utility functions and determine the best response strategy. In the case of 2 × 2 and N × M games, we are able to characterize all mixed equilibria. [ABSTRACT FROM AUTHOR]

Contrary to predictions from Expected Utility Theory and Game Theory, when making economic decisions in interpersonal situations, people take the interest of others into account and express various forms of solidarity, even in one-shot interactions with anonymous strangers. Research in other-regarding behavior is dominated by behavioral economical and evolutionary biological approaches. Psychological theory building, which addresses mental processes underlying other-regarding behavior, is rare. Based on Relational Models Theory (RMT, [1]) and Relationship Regulation Theory (RRT, [2]) it is proposed that moral motives influence individuals’ decision behavior in interpersonal situations via conscious and unconscious (automatic) processes. To test our propositions we developed the ‘Dyadic Solidarity Game’ and its solitary equivalent, the ‘Self-Insurance Game’. Four experiments, in which the moral motives “Unity” and “Proportionality” were manipulated, support the propositions made. First, it was shown that consciously activated moral motives (via framing of the overall goal of the experiment) and unconsciously activated moral motives (via subliminal priming) influence other-regarding behavior. Second, this influence was only found in interpersonal, not in solitary situations. Third, by combining the analyses of the two experimental games the extent to which participants apply the Golden Rule (“treat others how you wish to be treated”) could be established. Individuals with a “Unity” motive treated others like themselves, whereas individuals with a “Proportionality” motive gave others less then they gave themselves. The four experiments not only support the assumption that morals matter in economic games, they also deliver new insights in how morals matter in economic decision making. [ABSTRACT FROM AUTHOR]