activity
20242026
most citedMARCO: A Memory-Augmented Reinforcement Framework for Combinatorial Optimization

1 citations · 1 across the 6 of their papers we have counts for

collaborators

7 papers

cs.LG2026

Efficient Exploration Is Enough

Mikel Malagón, Jon Vadillo, Josu Ceberio +2

This work introduces an alternative view of efficient exploration and studies its theoretical and empirical implications in the absence of extrinsic rewards. Specifically, we defin…

cs.NE2026

Enabling Population-Based Architectures for Neural Combinatorial Optimization

Andoni Irazusta Garmendia, Josu Ceberio, Alexander Mendiburu

Neural Combinatorial Optimization (NCO) has mostly focused on learning policies, typically neural networks, that operate on a single candidate solution at a time, either by constru…

cs.LG2025

A Review on Single-Problem Multi-Attempt Heuristic Optimization

Judith Echevarrieta, Etor Arza, Aritz Pérez +1

In certain real-world optimization scenarios, practitioners are not interested in solving multiple problems but rather in finding the best solution to a single, specific problem. W…

cs.LG2025

Self-Composing Policies for Scalable Continual Reinforcement Learning

Mikel Malagón, Josu Ceberio, Jose A. Lozano

This work introduces a growable and modular neural network architecture that naturally avoids catastrophic forgetting and interference in continual reinforcement learning. The stru…

cs.NE2024★ 1 cited

MARCO: A Memory-Augmented Reinforcement Framework for Combinatorial Optimization

Andoni I. Garmendia, Quentin Cappart, Josu Ceberio +1

Neural Combinatorial Optimization (NCO) is an emerging domain where deep learning techniques are employed to address combinatorial optimization problems as a standalone solver. Des…

cs.AI2024

Craftium: Bridging Flexibility and Efficiency for Rich 3D Single- and Multi-Agent Environments

Mikel Malagón, Josu Ceberio, Jose A. Lozano

Advances in large models, reinforcement learning, and open-endedness have accelerated progress toward autonomous agents that can learn and interact in the real world. To achieve th…

cs.AI2024

Time to Stop and Think: What kind of research do we want to do?

Josu Ceberio, Borja Calvo

Experimentation is an intrinsic part of research in artificial intelligence since it allows for collecting quantitative observations, validating hypotheses, and providing evidence…