| Modeling, evaluation, and scale on artificial pedestrians: a literature review F Martinez-Gil, M Lozano, I García-Fernández, F Fernández ACM Computing Surveys (CSUR) 50 (5), 1-35, 2017 | 93 | 2017 |
| MARL-Ped: A multi-agent reinforcement learning based framework to simulate pedestrian groups F Martinez-Gil, M Lozano, F Fernández Simulation Modelling Practice and Theory 47, 259-275, 2014 | 70 | 2014 |
| Emergent behaviors and scalability for multi-agent reinforcement learning-based pedestrian models F Martinez-Gil, M Lozano, F Fernández Simulation Modelling Practice and Theory 74, 117-133, 2017 | 63 | 2017 |
| Multi-agent reinforcement learning for simulating pedestrian navigation F Martinez-Gil, M Lozano, F Fernández Adaptive and Learning Agents: International Workshop, ALA 2011, Held at …, 2012 | 54 | 2012 |
| Strategies for simulating pedestrian navigation with multiple reinforcement learning agents F Martinez-Gil, M Lozano, F Fernández Autonomous Agents and Multi-Agent Systems 29, 98-130, 2015 | 41 | 2015 |
| Clinically-driven virtual patient cohorts generation: an application to aorta P Romero, M Lozano, F Martínez-Gil, D Serra, R Sebastián, P Lamata, ... Frontiers in Physiology 12, 713118, 2021 | 30 | 2021 |
| Using inverse reinforcement learning with real trajectories to get more trustworthy pedestrian simulations F Martinez-Gil, M Lozano, I García-Fernández, P Romero, D Serra, ... Mathematics 8 (9), 1479, 2020 | 21 | 2020 |
| Calibrating a motion model based on reinforcement learning for pedestrian simulation F Martinez-Gil, M Lozano, F Fernández Motion in Games: 5th International Conference, MIG 2012, Rennes, France …, 2012 | 14 | 2012 |
| A Reinforcement Learning Approach for Multiagent Navigation. F Martinez-Gil, F Barber, M Lozano, F Grimaldo, F Fernández ICAART (1), 607-610, 2010 | 8 | 2010 |
| Reconstruction of the aorta geometry using canal surfaces P Romero, S Santos, R Sebastian, F Martinez-Gil, D Serra, P Calvillo, ... International Conference on Computational and Mathematical Biomedical …, 2019 | 6 | 2019 |
| Emergent collective behaviors in a multi-agent reinforcement learning pedestrian simulation: a case study F Martinez-Gil, M Lozano, F Fernández International Workshop on Multi-Agent Systems and Agent-Based Simulation …, 2014 | 4 | 2014 |
| MARL-Ped+ Hitmap: Towards improving agent-based simulations with distributed arrays E Rodriguez-Gutiez, F Martinez-Gil, JM Orduña, A Gonzalez-Escribano Algorithms and Architectures for Parallel Processing: ICA3PP 2016 Collocated …, 2016 | 2 | 2016 |
| Phase Space Data-Driven Simulation of Elastic Materials. C Monteagudo, M Lozano, I García-Fernández, F Martinez-Gil CEIG, 69-73, 2016 | 1 | 2016 |
| Reinforcement learning in a multi-agent framework for pedestrian simulation FA Martinez-Gil Universitat de Valencia (Spain), 2014 | 1 | 2014 |
| Agent's actions as a classification criteria for the state space in a learning from rewards system F Martinez-Gil Journal of Experimental & Theoretical Artificial Intelligence 20 (4), 269-276, 2008 | 1 | 2008 |
| Procedural Location of Roads Using Desire Paths. P Real, F Martínez-Gil, RJ Martínez-Durá, I García-Fernández CEIG, 19-24, 2019 | | 2019 |
| MARL-Ped+ Hitmap: Aumentando la productividad de simulaciones basadas en agentes con una herramienta de arrays distribuidos E Rodríguez Gutiez, F Martinez Gil, JM Orduña Huertas, ... Universidad de Salamanca, 2016 | | 2016 |
| Emergent collective behaviors in a multi-agent reinforcement learning based pedestrian simulation F Martinez-Gil, F Fernández, M Lozano RLDM 2013, 38, 2013 | | 2013 |
| Modeling, Evaluation and Scale on artificial Pedestrians: A literature F MARTINEZ-GIL, M LOZANO, I GARCÍA-FERNÁNDEZ, F FERNÁNDEZ | | |
