2 citations · 5 across the 9 of their papers we have counts for
10 papers
Control Systems with Model Hierarchies: A Category-Theoretic Framework
Baike She, Tyler Hanks, James Fairbanks +1
Storage functions are widely used to relate a control system to a simpler model for analysis and controller design, and to quantify model mismatch when a controller is designed on…
Heterogeneous Multi-Agent Multi-Target Tracking using Cellular Sheaves
Tyler Hanks, Cristian F. Nino, Joana Bou Barcelo +3
Multi-agent target tracking in the presence of nonlinear dynamics and agent heterogeneity, where state-space dimensions may differ, is a challenging problem that traditional graph…
Asynchronous Nonlinear Sheaf Diffusion for Multi-Agent Coordination
Yichen Zhao, Tyler Hanks, Hans Riess +3
Cellular sheaves and sheaf Laplacians provide a far-reaching generalization of graphs and graph Laplacians, resulting in a wide array of applications ranging from machine learning…
Distributed Multi-agent Coordination over Cellular Sheaves
Tyler Hanks, Hans Riess, Samuel Cohen +3
Techniques for coordination of multi-agent systems are vast and varied, often utilizing purpose-built solvers or controllers with tight coupling to the types of systems involved or…
A Compositional Framework for First-Order Optimization
Tyler Hanks, Matthew Klawonn, Evan Patterson +2
Optimization decomposition methods are a fundamental tool to develop distributed solution algorithms for large scale optimization problems arising in fields such as machine learnin…
Generalized Gradient Descent is a Hypergraph Functor
Tyler Hanks, James Fairbanks, Matthew Klawonn
Cartesian reverse derivative categories (CRDCs) provide an axiomatic generalization of the reverse derivative, which allows generalized analogues of classic optimization algorithms…
Characterizing Compositionality of LQR from the Categorical Perspective
Baike She, Tyler Hanks, James Fairbanks +1
Composing systems is a fundamental concept in modern control systems, yet it remains challenging to formally analyze how controllers designed for individual subsystems can differ f…
Modeling Model Predictive Control: A Category Theoretic Framework for Multistage Control Problems
Tyler Hanks, Baike She, Matthew Hale +3
Model predictive control (MPC) is an optimal control technique which involves solving a sequence of constrained optimization problems across a given time horizon. In this paper, we…
Compositional Exploration of Combinatorial Scientific Models
Kristopher Brown, Tyler Hanks, James Fairbanks
We implement a novel representation of model search spaces as diagrams over a category of models, where we have restricted attention to a broad class of models whose structure is p…
Computational category-theoretic rewriting
Kristopher Brown, Evan Patterson, Tyler Hanks +1
We demonstrate how category theory provides specifications that can efficiently be implemented via imperative algorithms and apply this to the field of graph rewriting. By examples…