Publications associées à Planification (intelligence artificielle)

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, Orcun Karaca

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, Kamalaruban Parameswaran, Luca Viano, Yu-Ting Huang

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, Vladislav Tempez

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