Private military services in the UK and Germany: Between partnership and regulation1

Controversial cases such as the aborted coup in Equatorial Guinea and the employment of private contractors in the Abu Ghraib prison have brought the proliferation of private ‘mercenaries’ to worldwide attention. However, the privatization of military security is more diverse and complex than generally suggested. Specifically, one needs to distinguish between the use of private mercenaries in developing countries and the privatization of military services in Europe. Focussing on the latter, this article proposes that the privatization of military services in industrialized countries can be understood in terms of a shift from ‘government’ to ‘governance’. As a consequence, the emergence of a private military industry in Europe is not only characterized by distinct forms of governance failure; European governments have also developed new modes of governance to control the industry. Using the United Kingdom and Germany as examples, this article examines two modes in particular: public private partnerships and governmental regulation

Living With Peak Discharge Uncertainty: The Self-learning Dike

Although river dikes still play a key role for flood protection in the Netherlands\ud there is a growing interest for other measures to deal with larger peak discharges, such as\ud lowering or widening the floodplains. Regardless of the strategy chosen the assessment of\ud its effect on the flood risk depends on the peak discharge statistics. A problem here is that\ud the statistical analysis of peak discharges relies on probability distributions based on the\ud limited time series of extreme discharges. The extrapolation of these distributions are\ud subject to considerable uncertainty, because there is a measuring record of only about 100\ud years and the natural variability can be expected to change as a result of climate change.\ud This raises the question whether a more direct response to the effects of climate change is\ud possible. The natural variability of the peak discharge changes, the changes in this\ud variability due to e.g. climate change and the new statistical distribution can only be\ud established after the actual change has happened. Even with regular updates of the\ud statistical distributions it is inherent that the actions taken to reduce the flood risk are not\ud anticipatory but delayed. As an alternative, this paper presents an adaptive or so-called selflearning\ud approach to deal with the uncertainty in the peak discharge statistics. The\ud difference with the probabilistic design of flood defense works, which depends on the\ud analysis and prediction of uncertain peak discharges, is that the dike is adapted in direct\ud response to peak water levels exceeding the dike height minus a certain safety margin. The\ud results indicate that, on average, adaptive flood management based on observed peak water\ud levels is at least as safe as a probabilistic approach, which necessarily relies on uncertain\ud discharge statistics. Other advantages of the adaptive strategy are also obvious: the rule of\ud response is simple and easy to communicate to the public, and peak water levels are less\ud difficult to measure. In general the example demonstrates that flood management can be\ud based on a direct response to the effects of climate change, without tedious statistical\ud analysis of peak discharge records

Utility Rate Equations of Group Population Dynamics in Biological and Social Systems

We present a novel system of equations to describe the evolution of self-organized structured societies (biological or human) composed of several trait groups. The suggested approach is based on the combination of ideas employed in the theory of biological populations, system theory, and utility theory. The evolution equations are defined as utility rate equations, whose parameters are characterized by the utility of each group with respect to the society as a whole and by the mutual utilities of groups with respect to each other. We analyze in detail the cases of two groups (cooperators and defectors) and of three groups (cooperators, defectors, and regulators) and find that, in a self-organized society, neither defectors nor regulators can overpass the maximal fractions of about 10% each. This is in agreement with the data for bee and ant colonies. The classification of societies by their distance from equilibrium is proposed. We apply the formalism to rank the countries according to the introduced metric quantifying their relative stability, which depends on the cost of defectors and regulators as well as their respective population fractions. We find a remarkable concordance with more standard economic ranking based, for instance, on GDP per capita.Comment: Latex file, 39 pages, 8 figure

The ecology of social interactions in online and offline environments

The rise in online social networking has brought about a revolution in social relations. However, its effects on offline interactions and its implications for collective well-being are still not clear and are under-investigated. We study the ecology of online and offline interaction in an evolutionary game framework where individuals can adopt different strategies of socialization. Our main result is that the spreading of self-protective behaviors to cope with hostile social environments can lead the economy to non-socially optimal stationary states

Near-Optimal Adversarial Policy Switching for Decentralized Asynchronous Multi-Agent Systems

A key challenge in multi-robot and multi-agent systems is generating solutions that are robust to other self-interested or even adversarial parties who actively try to prevent the agents from achieving their goals. The practicality of existing works addressing this challenge is limited to only small-scale synchronous decision-making scenarios or a single agent planning its best response against a single adversary with fixed, procedurally characterized strategies. In contrast this paper considers a more realistic class of problems where a team of asynchronous agents with limited observation and communication capabilities need to compete against multiple strategic adversaries with changing strategies. This problem necessitates agents that can coordinate to detect changes in adversary strategies and plan the best response accordingly. Our approach first optimizes a set of stratagems that represent these best responses. These optimized stratagems are then integrated into a unified policy that can detect and respond when the adversaries change their strategies. The near-optimality of the proposed framework is established theoretically as well as demonstrated empirically in simulation and hardware