Tootfinder

This https://arxiv.org/abs/2302.03977 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

On the Circuit Diameter Conjecture for Counterexamples to the Hirsch Conjecture
Circuit diameters of polyhedra are a fundamental tool for studying the complexity of circuit augmentation schemes for linear programming and for finding lower bounds on combinatorial diameters. The main open problem in this area is the circuit diameter conjecture, the analogue of the Hirsch conjecture in the circuit setting. A natural question is whether the well-known counterexamples to the Hirsch conjecture carry over. Previously, Stephen and Yusun showed that the Klee-Walkup counterexample t…

Regular Typed Unification
Jo\~ao Barbosa, M\'ario Florido, V\'itor Santos Costa
https://arxiv.org/abs/2404.16406 https://arxi…

Regular Typed Unification
Here we define a new unification algorithm for terms interpreted in semantic domains denoted by a subclass of regular types here called deterministic regular types. This reflects our intention not to handle the semantic universe as a homogeneous collection of values, but instead, to partition it in a way that is similar to data types in programming languages. We first define the new unification algorithm which is based on constraint generation and constraint solving, and then prove its main pro…

Expected Time-Optimal Control: a Particle MPC-based Approach via Sequential Convex Programming
Kazuya Echigo, Abhishek Cauligi, Beh\c{c}et A\c{c}{\i}kme\c{s}e
https://arxiv.org/abs/2404.16269

Expected Time-Optimal Control: a Particle MPC-based Approach via Sequential Convex Programming
In this paper, we consider the problem of minimum-time optimal control for a dynamical system with initial state uncertainties and propose a sequential convex programming (SCP) solution framework. We seek to minimize the expected terminal (mission) time, which is an essential capability for planetary exploration missions where ground rovers have to carry out scientific tasks efficiently within the mission timelines in uncertain environments. Our main contribution is to convert the underlying st…

A Cartesian Closed Category for Random Variables
Pietro Di Gianantonio, Abbas Edalat
https://arxiv.org/abs/2402.11727 https://arxiv.o…

A Cartesian Closed Category for Random Variables
We present a novel, yet rather simple construction within the traditional framework of Scott domains to provide semantics to probabilistic programming, thus obtaining a solution to a long-standing open problem in this area. Unlike current main approaches that employ some probability measures or continuous valuations on non-standard or rather complex structures, we use the Scott domain of random variables from a standard sample space -- the unit interval or the Cantor space -- to any given Scott…

Lightweight Syntactic API Usage Analysis with UCov
Gustave MonceLaBRI, Thomas CouturouLaBRI, Yasmine HamdaouiLaBRI, Thomas DegueuleLaBRI, Jean-R\'emy FalleriLaBRI, IUF
https://arxiv.org/abs/2402.12024

Lightweight Syntactic API Usage Analysis with UCov
Designing an effective API is essential for library developers as it is the lens through which clients will judge its usability and benefits, as well as the main friction point when the library evolves. Despite its importance, defining the boundaries of an API is a challenging task, mainly due to the diverse mechanisms provided by programming languages that have non-trivial interplays. In this paper, we present a novel conceptual framework designed to assist library maintainers in understanding…

Origami: (un)folding the abstraction of recursion schemes for program synthesis
Matheus Campos Fernandes, Fabricio Olivetti de Franca, Emilio Francesquini
https://arxiv.org/abs/2402.13828 https://arxiv.org/pdf/2402.13828
arXiv:2402.13828v1 Announce Type: new
Abstract: Program synthesis with Genetic Programming searches for a correct program that satisfies the input specification, which is usually provided as input-output examples. One particular challenge is how to effectively handle loops and recursion avoiding programs that never terminate. A helpful abstraction that can alleviate this problem is the employment of Recursion Schemes that generalize the combination of data production and consumption. Recursion Schemes are very powerful as they allow the construction of programs that can summarize data, create sequences, and perform advanced calculations. The main advantage of writing a program using Recursion Schemes is that the programs are composed of well defined templates with only a few parts that need to be synthesized. In this paper we make an initial study of the benefits of using program synthesis with fold and unfold templates, and outline some preliminary experimental results. To highlight the advantages and disadvantages of this approach, we manually solved the entire GPSB benchmark using recursion schemes, highlighting the parts that should be evolved compared to alternative implementations. We noticed that, once the choice of which recursion scheme is made, the synthesis process can be simplified as each of the missing parts of the template are reduced to simpler functions, which are further constrained by their own input and output types.

Optimization-based Heuristic for Vehicle Dynamic Coordination in Mixed Traffic Intersections
Muhammad Faris, Mario Zanon, Paolo Falcone
https://arxiv.org/abs/2404.14048

Optimization-based Heuristic for Vehicle Dynamic Coordination in Mixed Traffic Intersections
In this paper, we address a coordination problem for connected and autonomous vehicles (CAVs) in mixed traffic settings with human-driven vehicles (HDVs). The main objective is to have a safe and optimal crossing order for vehicles approaching unsignalized intersections. This problem results in a mixed-integer quadratic programming (MIQP) formulation which is unsuitable for real-time applications. Therefore, we propose a computationally tractable optimization-based heuristic that monitors plato…

Constraint Propagation on GPU: A Case Study for the Bin Packing Constraint
Fabio Tardivo, Laurent Michel, Enrico Pontelli
https://arxiv.org/abs/2402.14821 …

Constraint Propagation on GPU: A Case Study for the Bin Packing Constraint
The Bin Packing Problem is one of the most important problems in discrete optimization, as it captures the requirements of many real-world problems. Because of its importance, it has been approached with the main theoretical and practical tools. Resolution approaches based on Linear Programming are the most effective, while Constraint Programming proves valuable when the Bin Packing Problem is a component of a larger problem. This work focuses on the Bin Packing constraint and explores how GPUs…

A Cartesian Closed Category for Random Variables
Pietro Di Gianantonio, Abbas Edalat
https://arxiv.org/abs/2402.11727 https://arxiv.o…

A Cartesian Closed Category for Random Variables
We present a novel, yet rather simple construction within the traditional framework of Scott domains to provide semantics to probabilistic programming, thus obtaining a solution to a long-standing open problem in this area. Unlike current main approaches that employ some probability measures or continuous valuations on non-standard or rather complex structures, we use the Scott domain of random variables from a standard sample space -- the unit interval or the Cantor space -- to any given Scott…

This https://arxiv.org/abs/2308.15805 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Design of Coherent Passive Quantum Equalizers Using Robust Control Theory
The paper develops a methodology for the design of coherent equalizing filters for quantum communication channels. Given a linear quantum system model of a quantum communication channel, the aim is to obtain another quantum system which, when coupled with the original system, mitigates degrading effects of the environment. The main result of the paper is a systematic equalizer synthesis algorithm which relies on methods of state-space robust control design via semidefinite programming.

Origami: (un)folding the abstraction of recursion schemes for program synthesis
Matheus Campos Fernandes, Fabricio Olivetti de Franca, Emilio Francesquini
https://arxiv.org/abs/2402.13828 https://arxiv.org/pdf/2402.13828
arXiv:2402.13828v1 Announce Type: new
Abstract: Program synthesis with Genetic Programming searches for a correct program that satisfies the input specification, which is usually provided as input-output examples. One particular challenge is how to effectively handle loops and recursion avoiding programs that never terminate. A helpful abstraction that can alleviate this problem is the employment of Recursion Schemes that generalize the combination of data production and consumption. Recursion Schemes are very powerful as they allow the construction of programs that can summarize data, create sequences, and perform advanced calculations. The main advantage of writing a program using Recursion Schemes is that the programs are composed of well defined templates with only a few parts that need to be synthesized. In this paper we make an initial study of the benefits of using program synthesis with fold and unfold templates, and outline some preliminary experimental results. To highlight the advantages and disadvantages of this approach, we manually solved the entire GPSB benchmark using recursion schemes, highlighting the parts that should be evolved compared to alternative implementations. We noticed that, once the choice of which recursion scheme is made, the synthesis process can be simplified as each of the missing parts of the template are reduced to simpler functions, which are further constrained by their own input and output types.