Robustness

The standard theory of decision making under uncertainty advises the decision maker to form a statistical model linking outcomes to decisions and then to choose the optimal distribution of outcomes. This assumes that the decision maker trusts the model completely. But what should a decision maker do if the model cannot be trusted? Lars Hansen and Thomas Sargent, two leading macroeconomists, push the field forward as they set about answering this question. They adapt robust control techniques and apply them to economics. By using this theory to let decision makers acknowledge misspecification in economic modeling, the authors develop applications to a variety of problems in dynamic macroeconomics. Technical, rigorous, and self-contained, this book will be useful for macroeconomists who seek to improve the robustness of decision-making processes.decision-making, uncertainty, statistical models, control techniques, economic modeling, dynamic microeconomics, misspecification

Stochastic Robustness: Towards a Comprehensive Robustness Tool

Stochastic robustness is a simple technique to determine the robustness of linear, time-invariant systems by Monte Carlo methods. Stochastic stability robustness has been described previously. Those results are extended here to provide insight into control system design for performance. Together, stochastic stability and performance robustness concepts constitute a comprehensive tool that can be used to analyze control system robustness properties. As well, they offer control system design insight that can set the stage for stochastic robustness synthesis. The concept of stochastic stability robustness is reviewed, stochastic performance robustness is introduced, and stochastic robustness synthesis is described qualitatively. Confidence intervals necessary for comparing control laws statistically are presented

The Robustness of Quintessence

Recent observations seem to suggest that our Universe is accelerating implying that it is dominated by a fluid whose equation of state is negative. Quintessence is a possible explanation. In particular, the concept of tracking solutions permits to adress the fine-tuning and coincidence problems. We study this proposal in the simplest case of an inverse power potential and investigate its robustness to corrections. We show that quintessence is not affected by the one-loop quantum corrections. In the supersymmetric case where the quintessential potential is motivated by non-perturbative effects in gauge theories, we consider the curvature effects and the K\"ahler corrections. We find that the curvature effects are negligible while the K\"ahler corrections modify the early evolution of the quintessence field. Finally we study the supergravity corrections and show that they must be taken into account as $Q\approx m_{\rm Pl}$ at small red-shifts. We discuss simple supergravity models exhibiting the quintessential behaviour. In particular, we propose a model where the scalar potential is given by $V(Q)=\frac{\Lambda^{4+\alpha }}{Q^{\alpha}}e^{\frac{\kappa}{2}Q^2}$. We argue that the fine-tuning problem can be overcome if $\alpha \ge 11$. This model leads to $\omega_Q\approx -0.82$ for $\Omega_{\rm m}\approx 0.3$ which is in good agreement with the presently available data.Comment: 16 pages, 7 figure

Genralized Robustness of Entanglement

The robustness of entanglement results of Vidal and Tarrach considered the problem whereby an entangled state is mixed with a separable state so that the overall state becomes non-entangled. In general it is known that there are also cases when entangled states are mixed with other entangled states and where the sum is separable. In this paper, we treat the more general case where entangled states can be mixed with any states so that the resulting mixture is unentangled. It is found that entangled pure states for this generalized case have the same robustness as the restricted case of Vidal and Tarrach.Comment: Final version. Editorial changes and references added to independent wor

On the influence of topological characteristics on robustness of complex networks

In this paper, we explore the relationship between the topological characteristics of a complex network and its robustness to sustained targeted attacks. Using synthesised scale-free, small-world and random networks, we look at a number of network measures, including assortativity, modularity, average path length, clustering coefficient, rich club profiles and scale-free exponent (where applicable) of a network, and how each of these influence the robustness of a network under targeted attacks. We use an established robustness coefficient to measure topological robustness, and consider sustained targeted attacks by order of node degree. With respect to scale-free networks, we show that assortativity, modularity and average path length have a positive correlation with network robustness, whereas clustering coefficient has a negative correlation. We did not find any correlation between scale-free exponent and robustness, or rich-club profiles and robustness. The robustness of small-world networks on the other hand, show substantial positive correlations with assortativity, modularity, clustering coefficient and average path length. In comparison, the robustness of Erdos-Renyi random networks did not have any significant correlation with any of the network properties considered. A significant observation is that high clustering decreases topological robustness in scale-free networks, yet it increases topological robustness in small-world networks. Our results highlight the importance of topological characteristics in influencing network robustness, and illustrate design strategies network designers can use to increase the robustness of scale-free and small-world networks under sustained targeted attacks

Degeneracy: a link between evolvability, robustness and complexity in biological systems

A full accounting of biological robustness remains elusive; both in terms of the mechanisms by which robustness is achieved and the forces that have caused robustness to grow over evolutionary time. Although its importance to topics such as ecosystem services and resilience is well recognized, the broader relationship between robustness and evolution is only starting to be fully appreciated. A renewed interest in this relationship has been prompted by evidence that mutational robustness can play a positive role in the discovery of adaptive innovations (evolvability) and evidence of an intimate relationship between robustness and complexity in biology. This paper offers a new perspective on the mechanics of evolution and the origins of complexity, robustness, and evolvability. Here we explore the hypothesis that degeneracy, a partial overlap in the functioning of multi-functional components, plays a central role in the evolution and robustness of complex forms. In support of this hypothesis, we present evidence that degeneracy is a fundamental source of robustness, it is intimately tied to multi-scaled complexity, and it establishes conditions that are necessary for system evolvability