Although the definition of what empathetic preferences exactly are is still evolving, there is a general consensus in the psychology, science and engineering communities that the evolution toward players' behaviors in interactive decision-making problems will be accompanied by the exploitation of their empathy, sympathy, compassion, antipathy, spitefulness, selfishness, altruism, and self-abnegating states in the payoffs. In this article, we study one-shot bimatrix games from a psychological game theory viewpoint. A new empathetic payoff model is calculated to fit empirical observations and both pure and mixed equilibria are investigated. For a realized empathy structure, the bimatrix game is categorized among four generic class of games. Number of interesting results are derived. A notable level of involvement can be observed in the empathetic one-shot game compared the non-empathetic one and this holds even for games with dominated strategies. Partial altruism can help in breaking symmetry, in reducing payoff-inequality and in selecting social welfare and more efficient outcomes. By contrast, partial spite and self-abnegating may worsen payoff equity. Empathetic evolutionary game dynamics are introduced to capture the resulting empathetic evolutionarily stable strategies under wide range of revision protocols including Brown-von Neumann-Nash, Smith, imitation, replicator, and hybrid dynamics. Finally, mutual support and Berge solution are investigated and their connection with empathetic preferences are established. We show that pure altruism is logically inconsistent, only by balancing it with some partial selfishness does it create a consistent psychology.
In the 1880s, [pages 102-104] edge introduced the idea of other-regarding payoff transformations as follows: player @math maximizes the payoff function @math where @math Here @math and @math represent relative weights that @math assigns to @math (own) and @math (to the other player's) non-empathetic payoff, respectively. The work in @cite_9 proposed an interesting model of partial altruism as an explanation for the results of public good contribution games, where a player's utility is a linear function of both the player's own monetary payoff and the other players' payoffs. The work in @cite_4 @cite_2 proposed a model that uses both spite and altruism, where the adjusted utility of a player reflects the player's own utility and his regard for other players. A model of fairness is proposed in @cite_10 where in addition to purely selfish players, there are players who dislike inequitable outcomes.
@cite_10 @cite_9 @cite_4 @cite_2
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We consider a problem at the intersection of distributed computing and game theory, namely: Is it possible to achieve the "windfall of malice" even without the actual presence of malicious players? Our answer to this question is "Yes and No". Our positive result is that for the virus inoculation game, it is possible to achieve the windfall of malice by use of a mediator. Our negative result is that for symmetric congestion games that are known to have a windfall of malice, it is not possible to design a mediator that achieves this windfall. In proving these two results, we develop novel techniques for mediator design that we believe will be helpful for creating non-trivial mediators to improve social welfare in a large class of games. Environments with public goods are a wonderful playground for those interested in delicate experimental problems, serious theoretical challenges, and difficult mechanism design issues. A review is made of various public goods experiments. It is found that the public goods environment is a very sensitive one with much that can affect outcomes but are difficult to control. The many factors interact with each other in unknown ways. Nothing is known for sure. Environments with public goods present a serious challenge even to skilled experimentalists and many opportunities for imaginative work. We examine a simple theory of altruism in which players' payoffs are linear in their own monetary income and their opponents. The weight on the opponent's income is private information and varies in the population, depending, moreover, on what the opponent's coefficient is believed to be. Using results of ultimatum experiments and the final round of a centipede experiment, we are able to pin down relatively accurately what the distribution of altruism (and spite) in the population is. This distribution is then used with a reasonable degree of success to explain the results of the earlier rounds of centipede and the results of some public goods contribution games. In addition, we show that in a market game where the theory of selfish players does quite well, the theory of altruism makes exactly the same predictions as the theory of selfish players. (Copyright: Elsevier) With the explosive growth in wireless usage due in part to smart phones, tablets and a growing applications developer base, wireless operators are constantly looking for ways to increase the spectral efficiency of their networks with low power. Multiple input multiple output (MIMO) technology, which made its first broad commercial appearance in IEEE 802.11 systems, is now gaining substantial attention in mobile wireless wide area network with the launch of interoperable implementation of IEEE 802.16 and Long-Term Evolution networks. MIMO is a key technology in these networks which substantially improves network throughput, capacity and coverage. In this paper we investigate throughput sharing strategies in distributed massive MIMO network games where the users take into consideration not only their own throughout and risk but also the throughput of their neighborhood and subnetwork users. We provide equilibrium analysis and deduce the ex-post performance and network fairness. We show that, in presence of altruistic users, the sharing strategies improve the throughput fairness when the geodesic distance of the network is not large.