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In this paper, we show a new approach to transformations of an imperative program with function calls and global variables into a logically constrained term rewriting system. The resulting system represents transitions of the whole…

Logic in Computer Science · Computer Science 2019-02-25 Yoshiaki Kanazawa , Naoki Nishida

Stable matching is a fundamental area with many practical applications, such as centralised clearinghouses for school choice or job markets. Recent work has introduced the paradigm of near-feasibility in capacitated matching settings, where…

Computer Science and Game Theory · Computer Science 2026-02-12 Frederik Glitzner

We propose a computational framework to quantify (measure) and to optimize the reliability of complex systems. The approach uses a graph representation of the system that is subject to random failures of its components (nodes and edges).…

Optimization and Control · Mathematics 2021-06-25 Joshua L. Pulsipher , Victor M. Zavala

Abstract dynamic programming models are used to analyze $\lambda$-policy iteration with randomization algorithms. Particularly, contractive models with infinite policies are considered and it is shown that well-posedness of the…

Systems and Control · Electrical Eng. & Systems 2020-06-12 Yuchao Li , Karl H. Johansson , Jonas Mårtensson

We develop a dynamical systems approach to prioritizing and selecting multiple recurring tasks with the aim of conferring a degree of deliberative goal selection to a mobile robot confronted with competing objectives. We take navigation as…

Dynamical Systems · Mathematics 2018-03-12 Paul B. Reverdy , Daniel E. Koditschek

Cyber-physical systems, such as mobile robots, must respond adaptively to dynamic operating conditions. Effective operation of these systems requires that sensing and actuation tasks are performed in a timely manner. Additionally, execution…

Machine Learning · Computer Science 2012-03-19 Robert Glaubius , Terry Tidwell , Christopher Gill , William D. Smart

In this paper, we examine the convergence landscape of multi-agent learning under uncertainty. Specifically, we analyze two stochastic models of regularized learning in continuous games -- one in continuous and one in discrete time with the…

Computer Science and Game Theory · Computer Science 2025-12-10 Kyriakos Lotidis , Panayotis Mertikopoulos , Nicholas Bambos , Jose Blanchet

Stability is a fundamental concept that refers to a system's ability to return close to its original state after disturbances. The minimal conditions for stability when system parameters vary in time, though common in physics, have been…

Chaotic Dynamics · Physics 2026-05-22 Arnaud Lazarus , Emmanuel Trélat

We investigate the synchronization of active rotors. A rotor is composed of a free-rotating arm with a particle that releases a surface-active chemical compound. It exhibits self-rotation due to the surface tension gradient originating from…

Pattern Formation and Solitons · Physics 2023-06-28 Hiroyuki Kitahata , Yuki Koyano

The problem of assigning agents to tasks is a central computational challenge in many multi-agent autonomous systems. However, in the real world, agents are not always perfect and may fail due to a number of reasons. A motivating…

Robotics · Computer Science 2020-07-02 Russell Schwartz , Pratap Tokekar

This paper studies the well-posedness and regularity of safe stabilizing optimization-based controllers for control-affine systems in the presence of model uncertainty. When the system dynamics contain unknown parameters, a finite set of…

Optimization and Control · Mathematics 2024-01-01 Pol Mestres , Kehan Long , Nikolay Atanasov , Jorge Cortés

A two-state, three-dimensional, deterministic, reversible cellular automaton is shown to be capable of approximately circular orbits, wavelike undulations, and particle-like configurations that decay in accordance with a half-life law.

Cellular Automata and Lattice Gases · Physics 2012-06-12 Daniel B. Miller , Edward Fredkin

Learning how to learn efficiently is a fundamental challenge for biological agents and a growing concern for artificial ones. To learn effectively, an agent must regulate its learning speed, balancing the benefits of rapid improvement…

Machine Learning · Computer Science 2026-01-13 Valentina Njaradi , Rodrigo Carrasco-Davis , Peter E. Latham , Andrew Saxe

Adaptive optimal control using value iteration (VI) initiated from a stabilizing policy is theoretically analyzed in various aspects including the continuity of the result, the stability of the system operated using any single/constant…

Systems and Control · Computer Science 2015-05-18 Ali Heydari

In this article we analyze the optimal control strategy for rotating a monitored qubit from an initial pure state to an orthogonal state in minimum time. This strategy is described for two different cost functions of interest which do not…

Optimization and Control · Mathematics 2012-11-27 Srinivas Sridharan , Masahiro Yanagisawa , Joshua Combes

Living systems often function with regulatory interactions, but the question of how activity, stochasticity and regulations work together for achieving different goals still remains puzzling. We propose a stochastic model of an active…

Soft Condensed Matter · Physics 2026-03-02 Tai Han , Fanlong Meng

This article deals with the implementation of the Smith Predictor for state feedback control in state space representation. The desired control law, obtained using partial differential equations and backstepping control, contains an…

Systems and Control · Electrical Eng. & Systems 2025-12-03 Jesus-Pablo Toledo-Zucco , Frédéric Gouaisbaut , Gaetan Chapput

The ability of executing multiple tasks simultaneously is an important feature of redundant robotic systems. As a matter of fact, complex behaviors can often be obtained as a result of the execution of several tasks. Moreover, in…

Systems and Control · Electrical Eng. & Systems 2025-06-03 Gennaro Notomista , Mario Selvaggio , Francesca Pagano , María Santos , Siddharth Mayya , Vincenzo Lippiello , Cristian Secchi

This work provides a rigorous framework for studying continuous time control problems in uncertain environments. The framework considered models uncertainty in state dynamics as a measure on the space of functions. This measure is…

Optimization and Control · Mathematics 2018-02-22 Ryan Murray , Michele Palladino

We consider reachability in dynamical systems with discrete linear updates, but with fixed digital precision, i.e., such that values of the system are rounded at each step. Given a matrix $M \in \mathbb{Q}^{d \times d}$, an initial vector…

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