activity
20202025
most citedAMLSI: A Novel Accurate Action Model Learning Algorithm

2 citations · 3 across the 5 of their papers we have counts for

collaborators

5 papers

cs.RO2025

GAIPAT -Dataset on Human Gaze and Actions for Intent Prediction in Assembly Tasks

Maxence Grand, Damien Pellier, Francis Jambon

The primary objective of the dataset is to provide a better understanding of the coupling between human actions and gaze in a shared working environment with a cobot, with the aim…

cs.AI2022★ 1 cited

An Accurate HDDL Domain Learning Algorithm from Partial and Noisy Observations

M. Grand, H. Fiorino, D. Pellier

The Hierarchical Task Network ({\sf HTN}) formalism is very expressive and used to express a wide variety of planning problems. In contrast to the classical {\sf STRIPS} formalism…

cs.AI2022

HDDL 2.1: Towards Defining an HTN Formalism with Time

D. Pellier, H. Fiorino, M. Grand +2

Real world applications of planning, like in industry and robotics, require modelling rich and diverse scenarios. Their resolution usually requires coordinated and concurrent actio…

cs.AI2021

TempAMLSI : Temporal Action Model Learning based on Grammar Induction

Maxence Grand, Damien Pellier, Humbert Fiorino

Hand-encoding PDDL domains is generally accepted as difficult, tedious and error-prone. The difficulty is even greater when temporal domains have to be encoded. Indeed, actions hav…

cs.AI2020★ 2 cited

AMLSI: A Novel Accurate Action Model Learning Algorithm

Maxence Grand, Humbert Fiorino, Damien Pellier

This paper presents new approach based on grammar induction called AMLSI Action Model Learning with State machine Interactions. The AMLSI approach does not require a training datas…