Towards harmonizing competing models: Russian forests' net primary production case study

This paper deals with the issue of reconciling competing stochastic estimates provided by independent sources. We employ an integration method based on a principle of mutual compatibility of prior estimates. The method does not take into account credibility of the sources of the estimates, including their past performance. The quality of integration is evaluated in terms of change in the probability distribution. We use the method to integrate two types of estimates of the annual Net Primary Production (NPP) of the forest ecosystems in seven bioclimatic zones in Russia. The estimates are generated based on an empirical landscape-ecosystem approach and on an ensemble of dynamic global vegetation models; the gaps in thei estimates reach 23%. Elimination of the gaps may help better quantify the input of the terrestrial ecosystems to the global carbon cyce. The main result of this paper is the evidence of applicability of the method for selection a set of candidates for credible integrated estimates of uncertain ecological parameters (like forest NPP) integrating prior estimates

Assessing historical realibility of the agent-based model of the global energy system

This study looks at the historical reliability of the agent-based model of the global energy system. We present a mathematical framework for the agent-based model calibration and sensitivity analysis based on historical observations. Simulation consistency with the historical record is measured as a distance between two vectors of data points and inference on parameter values is done from the probability distribution of this stochastic estimate. Proposed methodology is applied to the model of the global energy system. Some model properties and limitations followed from calibration results are discussed

Dealing with femtorisks in international relations

The contemporary global community is increasingly interdependent and confronted with systemic risks posed by the actions and interactions of actors existing beneath the level of formal institutions, often operating outside effective governance structures. Frequently, these actors are human agents, such as rogue traders or aggressive financial innovators, terrorists, groups of dissidents, or unauthorized sources of sensitive or secret information about government or private sector activities. In other instances, influential .actors. take the form of climate change, communications technologies, or socioeconomic globalization. Although these individual forces may be small relative to state governments or international institutions, or may operate on long time scales, the changes they catalyze can pose significant challenges to the analysis and practice of international relations through the operation of complex feedbacks and interactions of individual agents and interconnected systems. We call these challenges "femtorisks," and emphasize their importance for two reasons. First, in isolation, they may be inconsequential and semiautonomous; but when embedded in complex adaptive systems, characterized by individual agents able to change, learn from experience, and pursue their own agendas, the strategic interaction between actors can propel systems down paths of increasing, even global, instability. Second, because their influence stems from complex interactions at interfaces of multiple systems (e.g., social, financial, political, technological, ecological, etc.), femtorisks challenge standard approaches to risk assessment, as higher-order consequences cascade across the boundaries of socially constructed complex systems. We argue that new approaches to assessing and managing systemic risk in international relations are required, inspired by principles of evolutionary theory and development of resilient ecological systems

TWO-STEP "WIN-STAY, LOSE-SHIFT" AND LEARNING TO COOPERATE IN THE REPEATED PRISONER'S DILEMMA

The standard win-stay, lose-shift behavior strategy in the repeated Prisoner's Dilemma game prescribes the players that win and lose in a current game round to keep and to change, respectively, their current actions, in the next round. Winning and losing are understood as receiving one of two upper values and one of two lower values, respectively, among the four admissible values for the players' benefits. In particular, a player acting as a cooperator against cooperation wins and therefore is not allowed to switch to defection in the next round with a hope to gain more (provided his/her rival keeps cooperating). This constraint can be viewed as too strong for a selfish player. Here, we discuss a two-step win-stay, lose-shift behavior that differs from the traditional win-stay lose-shift one in understanding of winning and losing. A player wins if his/her benefit is no smaller that in the previous round, and loses otherwise. This pattern is in a sense more selfish; in particular, a switch from cooperation (against cooperation) to defection is not forbidden. Another confirmation of a more selfish character of the two-step win-stay, lose-shift behavior, compared to the standard win-stay, lose-shift one, is that the former does not bring two individuals playing the repeated Prisoner's Dilemma game to mutual cooperation. In this paper, our goal is to understand to what degree one can relax the two-step win-stay, lose-shift behavior in selfishness so as to reach mutual cooperation, anyway. We deal with two models of the repeated Prisoner's Dilemma game — a game of two individuals and a game in a group of players. In the game of two individuals, a relaxed two-step win-stay, lose-shift behavior assumes that the players use mixed strategies; here, relaxation is associated with patience. In the game in a group of players, relaxation is achieved through conformity, a tendency to join the majority. We show that even a small degree of conformity is enough to teach a two-step win-stay, lose-shift group to cooperate.