The deployment of mobile ad-hoc networks involves several configuration steps, which complicate research efforts and hinder user interest. This problem prompts for new approaches offering full autoconfiguration of ter...
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The deployment of mobile ad-hoc networks involves several configuration steps, which complicate research efforts and hinder user interest. This problem prompts for new approaches offering full autoconfiguration of terminals at the different network layers involved. In this paper we propose a novel solution for the autoconfiguration of IEEE 802.11 based MANETs that relies on SSID parameter embedding. Our solution allows users to join an existing MANET without resorting to any additional technology, and even in the presence of encrypted communications. Experimental testbed results using a real implementation of the proposed solution show that it introduces significant improvements compared to other existing solutions, allowing nearby stations to be configured in about two seconds, and also enabling multi-hop dissemination of configuration data to take place quickly and efficiently.
One of the long-term goals in evolutionary robotics is to be able to automatically synthesize controllers for real autonomous robots based only on a task specification. While a number of studies have shown the applica...
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One of the long-term goals in evolutionary robotics is to be able to automatically synthesize controllers for real autonomous robots based only on a task specification. While a number of studies have shown the applicability of evolutionary robotics techniques for the synthesis of behavioral control, researchers have consistently been faced with a number of issues preventing the widespread adoption of evolutionary robotics for engineering purposes. In this article, we review and discuss the open issues in evolutionary robotics. First, we analyze the benefits and challenges of simulation-based evolution and subsequent deployment of controllers versusevolution on real robotic hardware. Second, we discuss specific evolutionary computation issues that have plagued evolutionary robotics: (1)the bootstrap problem, (2)deception, and (3)the role of genomic encoding and genotype-phenotype mapping in the evolution of controllers for complex tasks. Finally, we address the absence of standard research practices in the field. We also discuss promising avenues of research. Our underlying motivation is the reduction of the current gap between evolutionary robotics and mainstream robotics, and the establishment of evolutionary robotics as a canonical approach for the engineering of autonomous robots.
In this thesis, I present our attempts to formulate new bootstrap approaches to Quantum Field Theories. The main goal of these approaches is to offer complementary techniques to the Effective Field Theory paradigm. Na...
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In this thesis, I present our attempts to formulate new bootstrap approaches to Quantum Field Theories. The main goal of these approaches is to offer complementary techniques to the Effective Field Theory paradigm. Namely, techniques that allow one to constrain IR observables using UV knowledge. For example, we may assume the existence of a local UV completion or detailed information about a UV lattice description. The first approach we present utilizes S-matrix bootstrap to turn “experimental” data, the low energy scattering phase, into rigorous information about the existence or nonexistence of resonances in a two-dimensional theory of massive particles. As a zeroth step towards generalization to higher dimensions, we also report on progress in the study of scattering in Chern-Simons theory coupled to fundamental matter, which we hope will enable formulation of its S-matrix bootstrap problem in the near future. It will be the first S-matrix bootstrap problem studied in which Anyonic properties are directly involved. In order to set up the second approach, we have studied the line operators that can appear in the conformal Chern-Simons theory coupled to fundamental matter. Their endpoints are the Anyons of the conformal theory. The lines obey constraints from conformal symmetry and a set of loop equations which allow setting up a bootstrap for correlators of straight lines. In the third approach, we show that equations of motion together with reflection positivity severely constrain correlators of the Ising statistical model on the lattice. Namely, we derive rigorous two-sided bounds on spin correlators through semi-definite programming.
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