Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

This paper provides a theoretical framework for analysis of consensus algorithms for multi-agent networked systems with an emphasis on the role of directed information flow, robustness to changes in network topology due to link/node failures, time-delays, and performance guarantees. An overview of basic concepts of information consensus in networks and methods of convergence and performance analysis for the algorithms are provided. Our analysis framework is based on tools from matrix theory, algebraic graph theory, and control theory. We discuss the connections between consensus problems in networked dynamic systems and diverse applications including synchronization of coupled oscillators, flocking, formation control, fast consensus in small-world networks, Markov processes and gossip-based algorithms, load balancing in networks, rendezvous in space, distributed sensor fusion in sensor networks, and belief propagation. We establish direct connections between spectral and structural properties of complex networks and the speed of information diffusion of consensus algorithms. A brief introduction is provided on networked systems with nonlocal information flow that are considerably faster than distributed systems with lattice-type nearest neighbor interactions. Simulation results are presented that demonstrate the role of small-world effects on the speed of consensus algorithms and cooperative control of multivehicle formations

/pdf/consensus-and-cooperation-in-networked-multi-agent-systems-5ame7z72ny.pdf

Consensus and Cooperation in Networked Multi-Agent Systems

Data Mining Practical Machine Learning Tools and Techniques

This paper reviews some main results and progress in distributed multi-agent coordination, focusing on papers published in major control systems and robotics journals since 2006. Distributed coordination of multiple vehicles, including unmanned aerial vehicles, unmanned ground vehicles, and unmanned underwater vehicles, has been a very active research subject studied extensively by the systems and control community. The recent results in this area are categorized into several directions, such as consensus, formation control, optimization, and estimation. After the review, a short discussion section is included to summarize the existing research and to propose several promising research directions along with some open problems that are deemed important for further investigations.

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An Overview of Recent Progress in the Study of Distributed Multi-Agent Coordination

System Identification I

We address a cooling energy management problem in a multi-building setting where buildings need to maintain comfort conditions for the occupants by keeping their zones temperature within a certain range. To this purpose, each one of them has its own chiller and is connected to a shared cooling network. The goal is to minimize the overall district electricity cost over some finite time horizon by optimally setting the temperature set-points in the buildings and the energy exchange with the cooling network, compatibly with comfort and actuation constraints, while accounting for uncertainty, mainly due to outside temperature, people occupancy, and solar radiation. To this purpose, a distributed version of the scenario approach to stochastic constrained optimization is adopted, which allows to guarantee by design a predefined robustness level of the obtained solution against uncertainty.

/pdf/energy-management-in-a-multi-building-set-up-via-distributed-2s64ud8n9e.pdf

Energy management in a multi-building set-up via distributed stochastic optimization

The development of distributed real-time systems often relies on clock synchronization. However, achieving pre- cise synchronization in the field of Wireless Sensor Networks (WSNs) is hampered by c ...

FLOPSYNC-QACS : Quantization- Aware Clock Synchronization for Wireless Sensor Networks

http://www.nt.ntnu.no/users/skoge/prost/proceedings/ifac2014/media/files/0612.pdf

A randomized approach to space debris footprint characterization

We study feedback control for discrete-time linear time-invariant systems in presence of quantization both in the control action and in the measurement of the controlled variable. While in some application the quantization effects can be neglected, when high-precision control is needed, quantization has to be explicitly accounted for in control design. In this paper we propose a switched control solution for minimizing the effect of quantization of both the control and controlled variables in the case of a simple integrator with unitary delay, a model that is quite common in the computing systems domain. We show that the switched solution outperforms the one without switching, designed by neglecting quantization, and analyze necessary and sufficient conditions for the controlled system to exhibit periodic solutions in presence of an additive constant disturbance affecting the control input. Simulation results provide evidence of the effectiveness of the approach.

Maria Prandini

Papers

Energy management in a multi-building set-up via distributed stochastic optimization

FLOPSYNC-QACS : Quantization- Aware Clock Synchronization for Wireless Sensor Networks

A randomized approach to space debris footprint characterization

Switched control for quantized feedback systems: invariance and limit cycles analysis

A two-layer decentralized approach to the optimal energy management of a building district with a shared thermal storage