336 citations · 595 across the 19 of their papers we have counts for
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Towards a Unified Framework for Sequential Decision Making
Carlos Núñez-Molina, Pablo Mesejo, Juan Fernández-Olivares
In recent years, the integration of Automated Planning (AP) and Reinforcement Learning (RL) has seen a surge of interest. To perform this integration, a general framework for Seque…
On Using Admissible Bounds for Learning Forward Search Heuristics
Carlos Núñez-Molina, Masataro Asai, Pablo Mesejo +1
In recent years, there has been growing interest in utilizing modern machine learning techniques to learn heuristic functions for forward search algorithms. Despite this, there has…
A Review of Symbolic, Subsymbolic and Hybrid Methods for Sequential Decision Making
Carlos Núñez-Molina, Pablo Mesejo, Juan Fernández-Olivares
In the field of Sequential Decision Making (SDM), two paradigms have historically vied for supremacy: Automated Planning (AP) and Reinforcement Learning (RL). In the spirit of reco…
A Survey on Semi-Supervised Semantic Segmentation
Adrian Peláez-Vegas, Pablo Mesejo, Julián Luengo
Semantic segmentation is one of the most challenging tasks in computer vision. However, in many applications, a frequent obstacle is the lack of labeled images, due to the high cos…
NeSIG: A Neuro-Symbolic Method for Learning to Generate Planning Problems
Carlos Núñez-Molina, Pablo Mesejo, Juan Fernández-Olivares
In the field of Automated Planning there is often the need for a set of planning problems from a particular domain, e.g., to be used as training data for Machine Learning or as ben…