no code implementations • 17 Jul 2023 • Anubhav Singh, Miquel Ramirez, Nir Lipovetzky, Peter J. Stuckey
This paper studies the possibilities made open by the use of Lazy Clause Generation (LCG) based approaches to Constraint Programming (CP) for tackling sequential classical planning.
no code implementations • 28 Sep 2022 • Miquel Ramirez, Daniel Selvaratnam, Chris Manzie
This paper describes a revision of the classic Lazy Probabilistic Roadmaps algorithm (Lazy PRM), that results from pairing PRM and a novel Branch-and-Cut (BC) algorithm.
no code implementations • 7 Jul 2022 • Stefan O'Toole, Miquel Ramirez, Nir Lipovetzky, Adrian R. Pearce
We introduce a new algorithm, Regression based Supervised Learning (RSL), for learning per instance Neural Network (NN) defined heuristic functions for classical planning problems.
no code implementations • NeurIPS 2021 • Stefan O'Toole, Nir Lipovetzky, Miquel Ramirez, Adrian Pearce
We propose new width-based planning and learning algorithms inspired from a careful analysis of the design decisions made by previous width-based planners.
no code implementations • 17 May 2021 • Anubhav Singh, Nir Lipovetzky, Miquel Ramirez, Javier Segovia-Aguas
Width-based search algorithms seek plans by prioritizing states according to a suitably defined measure of novelty, that maps states into a set of novelty categories.
no code implementations • 13 Mar 2017 • Miquel Ramirez, Enrico Scala, Patrik Haslum, Sylvie Thiebaux
FS+ is shown to be a robust planner over a diverse set of hybrid domains, taken from the existing literature on hybrid planning and systems.
no code implementations • 19 May 2016 • Miquel Ramirez, Hector Geffner
In a recent paper, we have shown that Plan Recognition over STRIPS can be formulated and solved using Classical Planning heuristics and algorithms.