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

A continuous-time analysis of distributed stochastic gradient

We analyze the effect of synchronization on distributed stochastic gradient algorithms. By exploiting an analogy with dynamical models of biological quorum sensing -- where synchronization between agents is induced through communication with a common signal -- we quantify how synchronization can significantly reduce the magnitude of the noise felt by the individual distributed agents and by their spatial mean. This noise reduction is in turn associated with a reduction in the smoothing of the loss function imposed by the stochastic gradient approximation. Through simulations on model non-convex objectives, we demonstrate that coupling can stabilize higher noise levels and improve convergence. We provide a convergence analysis for strongly convex functions by deriving a bound on the expected deviation of the spatial mean of the agents from the global minimizer for an algorithm based on quorum sensing, the same algorithm with momentum, and the Elastic Averaging SGD (EASGD) algorithm. We discuss extensions to new algorithms which allow each agent to broadcast its current measure of success and shape the collective computation accordingly. We supplement our theoretical analysis with numerical experiments on convolutional neural networks trained on the CIFAR-10 dataset, where we note a surprising regularizing property of EASGD even when applied to the non-distributed case. This observation suggests alternative second-order in-time algorithms for non-distributed optimization that are competitive with momentum methods.Comment: 9/14/19 : Final version, accepted for publication in Neural Computation. 4/7/19 : Significant edits: addition of simulations, deep network results, and revisions throughout. 12/28/18: Initial submissio

Steganography: a class of secure and robust algorithms

This research work presents a new class of non-blind information hiding algorithms that are stego-secure and robust. They are based on some finite domains iterations having the Devaney's topological chaos property. Thanks to a complete formalization of the approach we prove security against watermark-only attacks of a large class of steganographic algorithms. Finally a complete study of robustness is given in frequency DWT and DCT domains.Comment: Published in The Computer Journal special issue about steganograph

Steganography: a Class of Algorithms having Secure Properties

Chaos-based approaches are frequently proposed in information hiding, but without obvious justification. Indeed, the reason why chaos is useful to tackle with discretion, robustness, or security, is rarely elucidated. This research work presents a new class of non-blind information hidingalgorithms based on some finite domains iterations that are Devaney's topologically chaotic. The approach is entirely formalized and reasons to take place into the mathematical theory of chaos are explained. Finally, stego-security and chaos security are consequently proven for a large class of algorithms.Comment: 4 pages, published in Seventh International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2011, Dalian, China, October 14-16, 201

Pareto Improving Price Regulation When the Asset Market Is Incomplete

When the asset market is incomplete, competitive equilibria are constrained suboptimal, which provides a scope for pareto improving interventions. Price regulation can be such a pareto improving policy, even when the welfare effects of rationing are taken into account. An appealing aspect of price regulation is that it that it operates anonymously on market variables. Fix-price equilibria exist under weak assumptions. Such equilibria permit a competitive analysis of an economy with an incomplete asset market that is out of equilibrium. Arbitrage opportunities may arise: with three or more assets actively traded, an individual may hold an arbitrage portfolio at equilibrium. The local existence of fix-price equilibrium for prices that are almost competitive may fail for robust examples. Under necessary and sufficient conditions for the local existence of fix-price equilibria, Pareto improving price regulation is generically possible.Incomplete asset market, fix-price equilibria, Pareto improvement

Tourism, Trade and Domestic Welfare

Tourism has been regarded as a major source of economic growth and a good source of foreign exchange earnings. Tourism has also been considered as an activity that imposes costs on the host country. Such costs include increased pollution, congestion and despoliation of fragile environments and intra-generational inequity aggravation. One aspect that has been ignored is the general equilibrium effects of tourism on the other sectors in the economy. These effects can be quite substantial and should be taken into account when assessing the net benefits of a tourism boom on an economy. This paper presents a model which captures the interdependence between tourism and the rest of the economy, in particular agriculture and manufacturing. We examine the effect of a tourist boom on structural adjustment, commodity and factor prices and more importantly resident welfare. An important result obtained is that the tourist boom may “immiserize” the residents. This occurs because of two effects. The first, a favourable effect due to an increase in the relative price of the non-traded good which is termed the secondary terms of trade effect. The second, a negative effect due to an efficiency loss that occurs in the presence of increasing returns to scale in manufacturing. If this second effect outweighs the first effect, resident immiserization occurs.Tourism, Trade welfare