Complementary External Resource Allocation to Information Security in Smart Cities

With the rapid development of technologies, such as big data, artificial intelligence, and cloud computing, the work cooperation among cities and the resources involved in business exchanges are deeply complementary. At the same time, information security has become one of the challenges for smart cities, which is ubiquitous and easy to cause public security issues. For this reason, this research modeled the actual problems and then made decisions on resource allocation by considering full cooperation and non-cooperation situations. Their influence with respect to city size, probability of intrusion by illegal users, and propagation probability of one-time intrusion were analyzed. Based on these foundation works, this research proposed incentive mechanisms to ensure the optimized information security for smart cities. These mechanisms ensure that cities not only voluntarily increase the intensity of resource allocation to information security, but also make the co-operation in line with the reality. Therefore, this balances the advantages and disadvantages of non-cooperation and full cooperation, so as to ensure that the information security level of urban agglomerations reaches the optimal state.

The evolution of indirect reciprocity under action and assessment generosity

Indirect reciprocity is a mechanism for the evolution of cooperation based on social norms. This mechanism requires that individuals in a population observe and judge each other’s behaviors. Individuals with a good reputation are more likely to receive help from others. Previous work suggests that indirect reciprocity is only effective when all relevant information is reliable and publicly available. Otherwise, individuals may disagree on how to assess others, even if they all apply the same social norm. Such disagreements can lead to a breakdown of cooperation. Here we explore whether the predominantly studied ‘leading eight’ social norms of indirect reciprocity can be made more robust by equipping them with an element of generosity. To this end, we distinguish between two kinds of generosity. According to assessment generosity, individuals occasionally assign a good reputation to group members who would usually be regarded as bad. According to action generosity, individuals occasionally cooperate with group members with whom they would usually defect. Using individual-based simulations, we show that the two kinds of generosity have a very different effect on the resulting reputation dynamics. Assessment generosity tends to add to the overall noise and allows defectors to invade. In contrast, a limited amount of action generosity can be beneficial in a few cases. However, even when action generosity is beneficial, the respective simulations do not result in full cooperation. Our results suggest that while generosity can favor cooperation when individuals use the most simple strategies of reciprocity, it is disadvantageous when individuals use more complex social norms.

Whitewashing Narratives: Israeli Media and the Framing of the Kidnapped Yemenite Babies Affair

This essay offers a review of ongoing media analysis of the kidnapped Yemenite Babies Affair in light of recent changes in public awareness since the emergence of social media and the more recent formal governmental recognition. It argues that the government’s efforts to silence this affair over decades would not have been possible without the media’s full cooperation. Moreover, the public denial of this affair contributes to the ongoing intra-Jewish rift and racism in Israeli society today. Questions regarding the reconciliation and remembrance of this affair in the public sphere will strongly influence the identity formation of Yemenite and Mizrahi children of future generations.

Kelly and Jackson networks with interchangeable, cooperative servers

In open Kelly and Jackson networks, servers are assigned to individual stations, serving customers only where they are assigned. We investigate the performance of modified networks where servers cooperate. A server who would be idle at the assigned station will serve customers at another station, speeding up service there. We assume interchangeable servers: the service rate of a server at a station depends only on the station, not the server. This gives work conservation, which is used in various ways. We investigate three levels of server cooperation, from full cooperation, where all servers are busy when there is work to do anywhere in the network, to one-way cooperation, where a server assigned to one station may assist a server at another, but not the converse. We obtain the same stability conditions for each level and, in a series of examples, obtain substantial performance improvement with server cooperation, even when stations before modification are moderately loaded.

Record-Keeping and Cooperation in Large Societies

We introduce a new model of repeated games in large populations with random matching, overlapping generations, and limited records of past play. We prove that steady-state equilibria exist under general conditions on records. When the updating of a player’s record can depend on the actions of both players in a match, any strictly individually rational action can be supported in a steady-state equilibrium. When record updates can depend only on a player’s own actions, fewer actions can be supported. Here we focus on the prisoner’s dilemma and restrict attention to strict equilibria that are coordination-proof, meaning that matched partners never play a Pareto-dominated Nash equilibrium in the one-shot game induced by their records and expected continuation payoffs. Such equilibria can support full cooperation if the stage game is either “strictly supermodular and mild” or “strongly supermodular,” and otherwise permit no cooperation at all. The presence of “supercooperator” records, where a player cooperates against any opponent, is crucial for supporting any cooperation when the stage game is “severe.”

Fractional Punishment of Free Riders to Improve Cooperation in Optional Public Good Games

Improving and maintaining cooperation are fundamental issues for any project to be time-persistent, and sanctioning free riders may be the most applied method to achieve it. However, the application of sanctions differs from one group (project or institution) to another. We propose an optional, public good game model where a randomly selected set of the free riders is punished. To this end, we introduce a parameter that establishes the portion of free riders sanctioned with the purpose to control the population state evolution in the game. This parameter modifies the phase portrait of the system, and we show that, when the parameter surpasses a threshold, the full cooperation equilibrium point becomes a stable global attractor. Hence, we demonstrate that the fractional approach improves cooperation while reducing the sanctioning cost.

Friendly-rivalry solution to the iterated n-person public-goods game

Repeated interaction promotes cooperation among rational individuals under the shadow of future, but it is hard to maintain cooperation when a large number of error-prone individuals are involved. One way to construct a cooperative Nash equilibrium is to find a ‘friendly-rivalry’ strategy, which aims at full cooperation but never allows the co-players to be better off. Recently it has been shown that for the iterated Prisoner’s Dilemma in the presence of error, a friendly rival can be designed with the following five rules: Cooperate if everyone did, accept punishment for your own mistake, punish defection, recover cooperation if you find a chance, and defect in all the other circumstances. In this work, we construct such a friendly-rivalry strategy for the iterated n-person public-goods game by generalizing those five rules. The resulting strategy makes a decision with referring to the previous m = 2n − 1 rounds. A friendly-rivalry strategy for n = 2 inherently has evolutionary robustness in the sense that no mutant strategy has higher fixation probability in this population than that of a neutral mutant. Our evolutionary simulation indeed shows excellent performance of the proposed strategy in a broad range of environmental conditions when n = 2 and 3.

Group cooperation against a hegemon

In this paper, I study the ability of a group of citizens to cooperate against a hegemon in a repeated contest game and where group members and the hegemon have different valuations of the prize. I first consider that group members use grim trigger strategies (GTSs) to support cooperative behavior and show that full cooperation within the group is more easily sustained as a stationary subgame perfect (Nash) equilibrium (SSPE) as either group size or the heterogeneity in the valuation of the prize increases. In turn, I show that full cooperation within the group can also be sustained as a weakly renegotiation-proof equilibrium (WRPE). However, an increase in group size makes it more difficult to sustain within-group cooperation, but an increase in the relative valuation of the prize by group members still facilitates group cooperation.

Friendly-rivalry solution to the iterated n-person public-goods game

Repeated interaction promotes cooperation among rational individuals under the shadow of future, but it is hard to maintain cooperation when a large number of error-prone individuals are involved. One way to construct a cooperative Nash equilibrium is to find a ‘friendly rivalry’ strategy, which aims at full cooperation but never allows the co-players to be better off. Recently it has been shown that for the iterated Prisoner’s Dilemma in the presence of error, a friendly rival can be designed with the following five rules: Cooperate if everyone did, accept punishment for your own mistake, punish defection, recover cooperation if you find a chance, and defect in all the other circumstances. In this work, we construct such a friendly-rivalry strategy for the iterated n-person public-goods game by generalizing those five rules. The resulting strategy makes a decision with referring to the previous m = 2n − 1 rounds. A friendly-rivalry strategy inherently has evolutionary robustness in the sense that no mutant strategy has higher fixation probability in this population than that of neutral drift, and our evolutionary simulation indeed shows excellent performance of the proposed strategy in a broad range of environmental conditions.Author summaryHow to maintain cooperation among a number of self-interested individuals is a difficult problem, especially if they can sometimes commit error. In this work, we propose a strategy for the iterated n-person public-goods game based on the following five rules: Cooperate if everyone did, accept punishment for your own mistake, punish others’ defection, recover cooperation if you find a chance, and defect in all the other circumstances. These rules are not far from actual human behavior, and the resulting strategy guarantees three advantages: First, if everyone uses it, full cooperation is recovered even if error occurs with small probability. Second, the player of this strategy always never obtains a lower long-term payoff than any of the co-players. Third, if the co-players are unconditional cooperators, it obtains a strictly higher long-term payoff than theirs. Therefore, if everyone uses this strategy, no one has a reason to change it. Furthermore, our simulation shows that this strategy will become highly abundant over long time scales due to its robustness against the invasion of other strategies. In this sense, the repeated social dilemma is solved for an arbitrary number of players.

Towards the digital land reclamation

The aim of the research is a retrospective analysis of the history and stages of development of digital land reclamation in Russia, the definition of «Digital land reclamation» and trends in its further development. In the framework of the retrospective analysis the main stages of melioration formation are determined. To achieve the maximum effect of the «digital reclamation» requires full cooperation of practical experience and scientific potential accumulated throughout the history of the reclamation complex, and the latest achievements of science and technology, which is currently possible only through the full digitalization of reclamation activities. The introduction of «digital reclamation» will achieve greater potential and effect in the modernization of the reclamation industry in the «hightech industry», through the use of innovative developments and optimal management decisions.