An Analysis of Adaptation as a Response to Climate Change

Climate change is likely to have relevant effects on our future socio-economic systems. It is therefore important to identify how markets and policy jointly react to expected climate change to protect our societies and well-being. This study addresses this issue by carrying out an integrated analysis of both optimal mitigation and adaptation at the global and regional level. Adaptation responses are disentangled into three different modes: reactive adaptation, proactive (or anticipatory) adaptation, and investments in innovation for adaptation purposes. The size, the timing, the relative contribution to total climate-related damage reduction, and the benefit-cost ratios of each of these strategies are assessed for the world as a whole, and for developed and developing countries in both a cooperative and a non-cooperative setting. The study also takes into account the role of price signals and markets in inducing and diffusing adaptation. This leads to two scenarios: A pessimistic one, in which policy-driven adaptation bears the burden, together with mitigation, of reducing climate damage; and an optimistic one, in which markets also autonomously contribute to reducing some damages by modifying sectoral structure, international trade flows, capital distribution and land allocation. For all scenarios, the costs and benefits of adaptation are assessed using WITCH, an integrated assessment, intertemporal optimization, forward-looking model. Extensive sensitivity analysis with respect to the size of climate damages and of the discount rate has also been carried out.Climate change impacts, mitigation, adaptation, integrated assessment model

Adaptive Modulation and Coding and Cooperative ARQ in a Cognitive Radio System

In this paper, a joint cross-layer design of adaptive modulation and coding (AMC) and cooperative automatic repeat request (C-ARQ) scheme is proposed for a secondary user in a shared-spectrum environment. First, based on the statistical descriptions of the channel, closed-form expressions of the average spectral efficiency (SE) and the average packet loss rate (PLR) are presented. Then, the cross-layer scheme is designed, with the aim of maximizing the average SE while maintaining the average PLR under a prescribed level. An optimization problem is formed, and a sub-optimal solution is found: the target packet error rates (PER) for the secondary system channels are obtained and the corresponding sub-optimal AMC rate adaptation policy is derived based on the target PERs. Finally, the average SE and the average PLR performance of the proposed scheme are presented

Cooperative Adaptive Control for Cloud-Based Robotics

This paper studies collaboration through the cloud in the context of cooperative adaptive control for robot manipulators. We first consider the case of multiple robots manipulating a common object through synchronous centralized update laws to identify unknown inertial parameters. Through this development, we introduce a notion of Collective Sufficient Richness, wherein parameter convergence can be enabled through teamwork in the group. The introduction of this property and the analysis of stable adaptive controllers that benefit from it constitute the main new contributions of this work. Building on this original example, we then consider decentralized update laws, time-varying network topologies, and the influence of communication delays on this process. Perhaps surprisingly, these nonidealized networked conditions inherit the same benefits of convergence being determined through collective effects for the group. Simple simulations of a planar manipulator identifying an unknown load are provided to illustrate the central idea and benefits of Collective Sufficient Richness.Comment: ICRA 201