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System identification of complex and nonlinear systems is a central problem for model predictive control and model-based reinforcement learning. Despite their complexity, such systems can often be approximated well by a set of linear…

Machine Learning · Statistics 2019-05-30 Philip Becker-Ehmck , Jan Peters , Patrick van der Smagt

In the load balancing problem, each node in a network is assigned a load, and the goal is to equally distribute the loads among the nodes, by preforming local load exchanges. While load balancing was extensively studied in static networks,…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-05-28 Seth Gilbert , Uri Meir , Ami Paz , Gregory Schwartzman

In this note, we provide complexity characterizations of model checking multi-pushdown systems. Multi-pushdown systems model recursive concurrent programs in which any sequential process has a finite control. We consider three standard…

Logic in Computer Science · Computer Science 2012-12-10 Kshitij Bansal , Stéphane Demri

We present a universal approach to the investigation of the dynamics in generalized models. In these models the processes that are taken into account are not restricted to specific functional forms. Therefore a single generalized models can…

Chaotic Dynamics · Physics 2007-05-23 Thilo Gross , Ulrike Feudel

The Douglas-Rachford (DR) algorithm is an iterative procedure that uses sequential reflections onto convex sets and which has become popular for convex feasibility problems. In this paper we propose a structural generalization that allows…

Optimization and Control · Mathematics 2018-07-18 Francisco J. Aragón Artacho , Yair Censor , Aviv Gibali

We present an algorithm to solve a system of diagonal polynomial equations over finite fields when the number of variables is greater than some fixed polynomial of the number of equations whose degree depends only on the degree of the…

Computational Complexity · Computer Science 2016-06-09 Gabor Ivanyos , Miklos Santha

We give a polynomial-time algorithm for learning latent-state linear dynamical systems without system identification, and without assumptions on the spectral radius of the system's transition matrix. The algorithm extends the recently…

Machine Learning · Computer Science 2018-02-13 Elad Hazan , Holden Lee , Karan Singh , Cyril Zhang , Yi Zhang

We investigate the computational complexity of the timed prediction problem in two-dimensional sandpile models. This question refines the classical prediction problem, which asks whether a cell q will eventually become unstable after adding…

Computational Complexity · Computer Science 2025-06-27 Pablo Concha-Vega , Kévin Perrot

This paper addresses the task allocation problem for multi-robot systems. The main issue with the task allocation problem is inherent complexity that makes finding an optimal solution within a reasonable time almost impossible. To hand the…

Multiagent Systems · Computer Science 2019-01-11 Hyo-Sang Shin , Teng Li , Pau Segui-Gasco

We consider geometric collision-detection problems for modular reconfigurable robots. Assuming the nodes (modules) are connected squares on a grid, we investigate the complexity of deciding whether collisions may occur, or can be avoided,…

Computational Geometry · Computer Science 2023-05-03 Siddharth Gupta , Marc van Kreveld , Othon Michail , Andreas Padalkin

This paper depicts algorithms for solving the decision Boolean Satisfiability Problem. An extreme problem is formulated to analyze the complexity of algorithms and the complexity for solving it. A novel and easy reformulation as a lottery…

Computational Complexity · Computer Science 2016-04-15 Carlos Barrón-Romero

A strongly polynomial algorithm is given for the generalized flow maximization problem. It uses a new variant of the scaling technique, called continuous scaling. The main measure of progress is that within a strongly polynomial number of…

Data Structures and Algorithms · Computer Science 2016-03-01 László A. Végh

Iterative load balancing algorithms for indivisible tokens have been studied intensively in the past. Complementing previous worst-case analyses, we study an average-case scenario where the load inputs are drawn from a fixed probability…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-03-28 Leran Cai , Thomas Sauerwald

The ability to learn polynomials and generalize out-of-distribution is essential for simulation metamodels in many disciplines of engineering, where the time step updates are described by polynomials. While feed forward neural networks can…

Machine Learning · Computer Science 2023-07-21 Jesper Hauch , Christoffer Riis , Francisco C. Pereira

We present a dynamic learning paradigm for "programming" a general quantum computer. A learning algorithm is used to find the control parameters for a coupled qubit system, such that the system at an initial time evolves to a state in which…

Quantum Physics · Physics 2008-08-12 E. C. Behrman , J. E. Steck , P. Kumar , K. A. Walsh

This paper proposes a control algorithm for stable implementation of asynchronous parallel quadratic programming (PQP) through dual decomposition technique. In general, distributed and parallel optimization requires synchronization of data…

Systems and Control · Electrical Eng. & Systems 2019-11-26 Kooktae Lee

A hybrid dynamical system switches between dynamic regimes at time- or state-triggered events. We propose an offline algorithm that simultaneously estimates discrete and continuous components of a hybrid system's state. We formulate state…

Optimization and Control · Mathematics 2019-05-23 Jize Zhang , Andrew M. Pace , Samuel A. Burden , Aleksandr Aravkin

Algorithms for the synchronisation of clocks across networks are both common and important within distributed systems. We here address not only the formal modelling of these algorithms, but also the formal verification of their behaviour.…

Logic in Computer Science · Computer Science 2018-09-28 Paul Gainer , Sven Linker , Clare Dixon , Ullrich Hustadt , Michael Fisher

We consider an LQR optimal control problem with partially unknown dynamics. We propose a new model-based online algorithm to obtain an approximation of the dynamics $and$ the control at the same time during a single simulation.

Numerical Analysis · Mathematics 2021-05-31 Agnese Pacifico , Andrea Pesare , Maurizio Falcone

Endowing the set of functional graphs (FGs) with the sum (disjoint union of graphs) and product (standard direct product on graphs) operations induces on FGs a structure of a commutative semiring R. The operations on R can be naturally…

Discrete Mathematics · Computer Science 2025-11-26 Alberto Dennunzio , Enrico Formenti , Luciano Margara , Sara Riva