50 citations · 51 across the 6 of their papers we have counts for
6 papers
Scaling up ML-based Black-box Planning with Partial STRIPS Models
Matias Greco, Álvaro Torralba, Jorge A. Baier +1
A popular approach for sequential decision-making is to perform simulator-based search guided with Machine Learning (ML) methods like policy learning. On the other hand, model-rela…
Exploiting Learned Policies in Focal Search
Pablo Araneda, Matias Greco, Jorge A. Baier
Recent machine-learning approaches to deterministic search and domain-independent planning employ policy learning to speed up search. Unfortunately, when attempting to solve a sear…
How a General-Purpose Commonsense Ontology can Improve Performance of Learning-Based Image Retrieval
Rodrigo Toro Icarte, Jorge A. Baier, Cristian Ruz +1
The knowledge representation community has built general-purpose ontologies which contain large amounts of commonsense knowledge over relevant aspects of the world, including usefu…
Evaluating navigational RDF queries over the Web
Jorge Baier, Dietrich Daroch, Juan Reutter +1
Semantic Web, and its underlying data format RDF, lend themselves naturally to navigational querying due to their graph-like structure. This is particularly evident when considerin…
Finite LTL Synthesis is EXPTIME-complete
Jorge A. Baier, Alberto Camacho, Christian Muise +1
LTL synthesis -- the construction of a function to satisfy a logical specification formulated in Linear Temporal Logic -- is a 2EXPTIME-complete problem with relevant applications…
Avoiding and Escaping Depressions in Real-Time Heuristic Search
Carlos Hernández, Jorge A Baier
Heuristics used for solving hard real-time search problems have regions with depressions. Such regions are bounded areas of the search space in which the heuristic function is inac…