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In this paper, we address complexity issues for timeline-based planning over dense temporal domains. The planning problem is modeled by means of a set of independent, but interacting, components, each one represented by a number of state…

Logic in Computer Science · Computer Science 2018-09-11 Laura Bozzelli , Alberto Molinari , Angelo Montanari , Adriano Peron

Qualitative timeline-based planning models domains as sets of independent, but interacting, components whose behaviors over time, the timelines, are governed by sets of qualitative temporal constraints (ordering relations), called…

Artificial Intelligence · Computer Science 2026-03-31 Dario Della Monica , Angelo Montanari , Pietro Sala

A weighted version of the parareal method for parallel-in-time computation of time dependent problems is presented. Linear stability analysis for a scalar weighing strategy shows that the new scheme may enjoy favorable stability properties…

Numerical Analysis · Mathematics 2018-02-09 Gil Ariel , Hieu Nguyen , Richard Tsai

In this paper, we address the problem of synthesizing optimal path plans in a 2D subject to spatio-temporal and thermal constraints. Our solution consists of reducing the path planning problem to a Mixed Integer Linear Programming (MILP)…

Robotics · Computer Science 2020-07-21 Zahra Rahimi Afzal , Pavana Prabhakar , Pavithra Prabhakar

In this paper, the use of partitioned linear multistep methods (PLMM) as time integrators for the numerical approximation of some partial differential equations (pdes) is studied. We consider the periodic initial-value problem of two…

Numerical Analysis · Mathematics 2025-11-06 Begoña Cano , Angel Durán , Melquíades Rodríguez

Task and Motion Planning has made great progress in solving hard sequential manipulation problems. However, a gap between such planning formulations and control methods for reactive execution remains. In this paper we propose a model…

Robotics · Computer Science 2022-09-23 Marc Toussaint , Jason Harris , Jung-Su Ha , Danny Driess , Wolfgang Hönig

In this paper we generalize the Interior Point-Proximal Method of Multipliers (IP-PMM) presented in [An Interior Point-Proximal Method of Multipliers for Convex Quadratic Programming, Computational Optimization and Applications, 78,…

Optimization and Control · Mathematics 2021-09-09 Spyridon Pougkakiotis , Jacek Gondzio

Motion planning with simple objectives, such as collision-avoidance and goal-reaching, can be solved efficiently using modern planners. However, the complexity of the allowed tasks for these planners is limited. On the other hand, signal…

Robotics · Computer Science 2025-03-05 Wenliang Liu , Nathalie Majcherczyk , Federico Pecora

Motion planning classically concerns the problem of accomplishing a goal configuration while avoiding obstacles. However, the need for more sophisticated motion planning methodologies, taking temporal aspects into account, has emerged. To…

Systems and Control · Computer Science 2017-03-08 Lars Lindemann , Dimos V. Dimarogonas

Sequential recommender systems have demonstrated a huge success for next-item recommendation by explicitly exploiting the temporal order of users' historical interactions. In practice, user interactions contain more useful temporal…

Information Retrieval · Computer Science 2023-07-25 Chen Rui , Liang Guotao , Ma Chenrui , Han Qilong , Li Li , Huang Xiao

Multivariate time-series (MTS) forecasting is a paramount and fundamental problem in many real-world applications. The core issue in MTS forecasting is how to effectively model complex spatial-temporal patterns. In this paper, we develop a…

Machine Learning · Computer Science 2024-02-16 Jinliang Deng , Xiusi Chen , Renhe Jiang , Du Yin , Yi Yang , Xuan Song , Ivor W. Tsang

We consider the problem of computing numerical invariants of programs by abstract interpretation. Our method eschews two traditional sources of imprecision: (i) the use of widening operators for enforcing convergence within a finite number…

Programming Languages · Computer Science 2015-05-27 Thomas Martin Gawlitza , David Monniaux

Learning-based methods have shown promising performance for accelerating motion planning, but mostly in the setting of static environments. For the more challenging problem of planning in dynamic environments, such as multi-arm assembly…

Robotics · Computer Science 2025-06-13 Ruipeng Zhang , Chenning Yu , Jingkai Chen , Chuchu Fan , Sicun Gao

We introduce the notion of "\delta-complete decision procedures" for solving SMT problems over the real numbers, with the aim of handling a wide range of nonlinear functions including transcendental functions and solutions of…

Logic in Computer Science · Computer Science 2012-09-18 Sicun Gao , Jeremy Avigad , Edmund Clarke

Automated planning using a symbolic planning language, such as PDDL, is a general approach to producing optimal plans to achieve a stated goal. However, creating suitable machine understandable descriptions of the planning domain, problem,…

Artificial Intelligence · Computer Science 2025-10-10 Owen Burns , Dana Hughes , Katia Sycara

Spatio-temporal forecasting is pivotal in numerous real-world applications, including transportation planning, energy management, and climate monitoring. In this work, we aim to harness the reasoning and generalization abilities of…

Machine Learning · Computer Science 2025-06-24 Hao Wang , Jindong Han , Wei Fan , Leilei Sun , Hao Liu

Multi-sector capacity expansion models play a crucial role in energy planning by providing decision support for policymaking in technology development. To ensure reliable support, these models require high technological, spatial, and…

Optimization and Control · Mathematics 2025-04-14 Federico Parolin , Yu Weng , Paolo Colbertaldo , Ruaridh Macdonald

We give a polynomial time, $(1+\epsilon)$-approximation algorithm for the traveling repairman problem (TRP) in the Euclidean plane and on weighted trees. This improves on the known quasi-polynomial time approximation schemes for these…

Data Structures and Algorithms · Computer Science 2014-09-22 René Sitters

We introduce a method for real-time navigation and tracking with differentiably rendered world models. Learning models for control has led to impressive results in robotics and computer games, but this success has yet to be extended to…

Machine Learning · Computer Science 2022-01-26 Baris Kayalibay , Atanas Mirchev , Patrick van der Smagt , Justin Bayer

The increasing relevance of areas such as real-time and embedded systems, pervasive computing, hybrid systems control, and biological and social systems modeling is bringing a growing attention to the temporal aspects of computing, not only…

General Literature · Computer Science 2013-08-15 Carlo A. Furia , Dino Mandrioli , Angelo Morzenti , Matteo Rossi