8 citations · 17 across the 16 of their papers we have counts for
20 papers
Deceptive Stochastic Patrolling via Markov Chain Lifting
Yohan John, Gilberto Diaz-Garcia, Jason R. Marden +1
In this paper we propose lifted Markov Chains (MCs) as a new paradigm for deriving patrol strategies for mobile agents on an environment represented as a graph. Lifted MCs operate…
Structured LLM Reasoning for Zero-Shot Human--Robot Coordination Under Hidden Goals
Dong Hae Mangalindan, Anand Gokhale, Francesco Bullo +1
We present a structured large-language-model (LLM) architecture for zero-shot human--robot coordination in a cooperative construction task with private goal views. Guided by a Dec-…
Regularized Model Predictive Control via Contractivity and Implicit Lur'e Analysis
Ryotaro Shima, Anand Gokhale, Alexander Davydov +1
This paper develops a contraction-based stability analysis for regularized model predictive control (MPC), whose feedback law is defined implicitly by a finite-horizon optimal cont…
An Energy-Based Mechanism for Compositional Behavior
Francesca Rossi, Veronica Centorrino, Francesco Bullo +1
Flexible intelligence relies on the ability to reuse previously acquired behaviors and combine them differently as circumstances change. In biological and artificial systems, this…
LogicGuard: Improving Embodied LLM agents through Temporal Logic based Critics
Anand Gokhale, Vaibhav Srivastava, Francesco Bullo
Large language models (LLMs) have shown promise in zero-shot and single step reasoning and decision making problems, but in long horizon sequential planning tasks, their errors com…
Similarity Matching Networks: Hebbian Learning and Convergence Over Multiple Time Scales
Veronica Centorrino, Francesco Bullo, Giovanni Russo
A recent breakthrough in biologically-plausible normative frameworks for dimensionality reduction is based upon the similarity matching cost function and the low-rank matrix approx…
Sampled-data Systems: Stability, Contractivity and Single-iteration Suboptimal MPC
Yiting Chen, Francesco Bullo, Emiliano Dall'Anese
This paper analyzes the stability of interconnected continuous-time (CT) and discrete-time (DT) systems coupled through sampling and zero-order hold mechanisms. The DT system updat…
Contractivity Analysis and Control Design for Lur'e Systems: Lipschitz, Incrementally Sector Bounded, and Monotone Nonlinearities
Ryotaro Shima, Alexander Davydov, Francesco Bullo
In this paper, we study the contractivity of Lur'e dynamical systems whose nonlinearity is either Lipschitz, incrementally sector bounded, or monotone. We consider both the discret…
Learning to Lie: Reinforcement Learning Attacks Damage Human-AI Teams and Teams of LLMs
Abed Kareem Musaffar, Anand Gokhale, Sirui Zeng +4
As artificial intelligence (AI) assistants become more widely adopted in safety-critical domains, it becomes important to develop safeguards against potential failures or adversari…
Proximal Gradient Dynamics and Feedback Control for Equality-Constrained Composite Optimization
Veronica Centorrino, Francesca Rossi, Francesco Bullo +1
This paper studies equality-constrained composite minimization problems. This class of problems, capturing regularization terms and inequality constraints, naturally arises in a wi…
Proximal Gradient Dynamics: Monotonicity, Exponential Convergence, and Applications
Anand Gokhale, Alexander Davydov, Francesco Bullo
In this letter we study the proximal gradient dynamics. This recently-proposed continuous-time dynamics solves optimization problems whose cost functions are separable into a nonsm…
Strategic Coalitions in Networked Contest Games
Gilberto Diaz-Garcia, Francesco Bullo, Jason R. Marden
In competitive resource allocation formulations multiple agents compete over different contests by committing their limited resources in them. For these settings, contest games off…
Exponential Stability of Parametric Optimization-Based Controllers via Lur'e Contractivity
Alexander Davydov, Francesco Bullo
In this letter, we investigate sufficient conditions for the exponential stability of LTI systems driven by controllers derived from parametric optimization problems. Our primary f…
Perspectives on Contractivity in Control, Optimization, and Learning
Alexander Davydov, Francesco Bullo
Contraction theory is a mathematical framework for studying the convergence, robustness, and modularity properties of dynamical systems and algorithms. In this opinion paper, we pr…
On Weakly Contracting Dynamics for Convex Optimization
Veronica Centorrino, Alexander Davydov, Anand Gokhale +2
We analyze the convergence behavior of \emph{globally weakly} and \emph{locally strongly contracting} dynamics. Such dynamics naturally arise in the context of convex optimization…
Learning Neural Contracting Dynamics: Extended Linearization and Global Guarantees
Sean Jaffe, Alexander Davydov, Deniz Lapsekili +2
Global stability and robustness guarantees in learned dynamical systems are essential to ensure well-behavedness of the systems in the face of uncertainty. We present Extended Line…
Multiplayer Homicidal Chauffeur Reach-Avoid Games: A Pursuit Enclosure Function Approach
Rui Yan, Xiaoming Duan, Rui Zou +3
This paper presents a multiplayer Homicidal Chauffeur reach-avoid differential game, which involves Dubins-car pursuers and simple-motion evaders. The goal of the pursuers is to co…
Positive Competitive Networks for Sparse Reconstruction
Veronica Centorrino, Anand Gokhale, Alexander Davydov +2
We propose and analyze a continuous-time firing-rate neural network, the positive firing-rate competitive network (\pfcn), to tackle sparse reconstruction problems with non-negativ…
Online Feedback Optimization and Singular Perturbation via Contraction Theory
Liliaokeawawa Cothren, Francesco Bullo, Emiliano Dall'Anese
In this paper, we provide a novel contraction-theoretic approach to analyze two-time scale systems, including those commonly encountered in Online Feedback Optimization (OFO). Our…
Contractivity of Distributed Optimization and Nash Seeking Dynamics
Anand Gokhale, Alexander Davydov, Francesco Bullo
In this letter, we study distributed optimization and Nash equilibrium-seeking dynamics from a contraction theoretic perspective. Our first result is a novel bound on the logarithm…