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Concept

Automated planning and scheduling

Related publications (18)

Augmenting large language models with chemistry tools

Philippe Schwaller, Oliver Tobias Schilter, Andres Camilo Marulanda Bran, Carlo Baldassari

Large language models (LLMs) have shown strong performance in tasks across domains but struggle with chemistry-related problems. These models also lack access to external knowledge sources, limiting their usefulness in scientific applications. We introduce ...

Nature Portfolio2024

Multi-robot task allocation for safe planning against stochastic hazard dynamics

Maryam Kamgarpour

We address multi-robot safe mission planning in uncertain dynamic environments. This problem arises in several applications including safety-critical exploration, surveillance, and emergency rescue missions. Computation of a multi-robot optimal control pol ...

IEEE2023

From C/C plus plus Code to High-Performance Dataflow Circuits

Paolo Ienne, Andrea Guerrieri, Lana Josipovic

High-level synthesis (HLS) tools typically generate statically scheduled datapaths. Static scheduling implies that the resulting circuits have a hard time exploiting parallelism in code with potential memory dependences, with control dependences, or where ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Robust Inverse Reinforcement Learning under Transition Dynamics Mismatch

Volkan Cevher, Luca Viano, Kamalaruban Parameswaran

We study the inverse reinforcement learning (IRL) problem under a transition dynamics mismatch between the expert and the learner. Specifically, we consider the Maximum Causal Entropy (MCE) IRL learner model and provide a tight upper bound on the learner’s ...

2021

Reference tracking stochastic model predictive control over unreliable channels and bounded control actions

Colin Neil Jones

A stochastic model predictive control framework over unreliable Bernoulli communication channels, in the presence of unbounded process noise and under bounded control inputs, is presented for tracking a reference signal. The data losses in the control chan ...

2021

Consistent Tomography Under Partial Observations Over Adaptive Networks

Ali H. Sayed

This paper studies the problem of inferring whether an agent is directly influenced by another agent over a network. Agent i influences agent j if they are connected (according to the network topology), and if agent j uses the data from agent i to update i ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2019

Exploring The Borderlands Of The Gathering Problem

Rachid Guerraoui, El Mahdi El Mhamdi, Alexandre David Olivier Maurer

Problems of pattern formation have been extensively studied in distributed computing. One of this problems is the gathering problem: agents must gather at a same position in a distributed manner. When gathering is not possible, a close problem is the conve ...

2019

Consistent Tomography over Diffusion Networks under the Low-Observability Regime

Ali H. Sayed, Augusto José Rabelo Almeida Santos

This work considers a diffusion network responding to streaming data, and studies the problem of identifying the topology of a subnetwork of observable agents by tracking their output measurements. Topology inference from indirect and/or incomplete dataset ...

IEEE2018

Impacts of Constraints and Constraint Handling Strategies for Multi-Objective Mechanical Design Problems

Jürg Alexander Schiffmann, Cyril Picard

Multi-objective optimization tools are becoming increasingly popu-lar in mechanical engineering and allow decision-makers to better understand the inevitable trade-offs. Mechanical design problems can however combine properties that make the use of optimiz ...

2018

STEP-NC compliant process planning of additive manufacturing: remanufacturing

Ian Anthony Stroud, Jumyung Um

Additive manufacturing is becoming one of the key methods for reproducing repair sections in remanufacturing processes. The major advantage of using additive processes is to minimize production time and waste. However, the surface quality and shape accurac ...

Springer London Ltd2017

Adaptive Prioritized Random Linear Coding and Scheduling for Layered Data Delivery from Multiple Servers

Pascal Frossard, Nikolaos Thomos, Eymen Kurdoglu

In this paper, we deal with the problem of jointly determining the optimal coding strategy and the scheduling decisions when receivers obtain layered data from multiple servers. The layered data is encoded by means of prioritized random linear coding (PRLC ...

Ieee-Inst Electrical Electronics Engineers Inc2015

A Decision Procedure for Regular Membership and Length Constraints over Unbounded Strings

Andrew Joseph Reynolds

We prove that the quantifier-free fragment of the theory of character strings with regular language membership constraints and linear integer constraints over string lengths is decidable. We do that by describing a sound, complete and terminating tableaux ...

Springer-Verlag Berlin2015

Learning search polices from humans in a partially observable context

Aude Billard, Guillaume Pierre Luc De Chambrier

Decision making and planning for which the state information is only partially available is a problem faced by all forms of intelligent entities they being either virtual, synthetic or biological. The standard approach to mathematically solve such a decisi ...

2014

Correlation-Aware Packet Scheduling in Multi-Camera Networks

Pascal Frossard, Laura Toni, Thomas Maugey

In multiview applications, multiple cameras acquire the same scene from different viewpoints and produce correlated video streams. This results in large amounts of highly redundant data. In order to save resources, it is critical to handle properly this co ...

Ieee-Inst Electrical Electronics Engineers Inc2014

Santa Claus Schedules Jobs On Unrelated Machines

Ola Nils Anders Svensson

One of the classic results in scheduling theory is the 2-approximation algorithm by Lenstra, Shmoys, and Tardos for the problem of scheduling jobs to minimize makespan on unrelated machines; i.e., job j requires time p(ij) if processed on machine i. More t ...

Siam Publications2012

Measurement Scheduling for Soil Moisture Sensing: From Physical Models to Optimal Control

David Shuman, Ke Li

In this paper, we consider the problem of monitoring soil moisture evolution using a wireless network of in situ sensors. Continuously sampling moisture levels with these sensors incurs high-maintenance and energy consumption costs, which are particularly ...

2010

Path planning versus cue responding: a bioinspired model of switching between navigation strategies

Ricardo Andres Chavarriaga Lozano

In this paper we describe a new computational model of switching between path-planning and cue-guided navigation strategies. It is based on three main assumptions: (i) the strategies are mediated by separate memory systems that learn independently and in p ...

Springer Verlag2010

Power Control for Target Tracking in Sensor Networks

Razvan Cristescu, Jean-Paul Wagner

We consider the problem of a sensor network tracking a moving target that exhibits a Markov model of mobility. The sensor nodes have adjustable power levels and the precision of the measurement of the target location depends on both the relative distance f ...

2005