Francisco Martinez Gil
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Citado por
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Año
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
402014
Multi-agent reinforcement learning for simulating pedestrian navigation
F Martinez-Gil, M Lozano, F Fernández
International Workshop on Adaptive and Learning Agents, 54-69, 2011
312011
Strategies for simulating pedestrian navigation with multiple reinforcement learning agents
F Martinez-Gil, M Lozano, F Fernández
Autonomous Agents and Multi-Agent Systems 29 (1), 98-130, 2015
232015
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
212017
Emergent behaviors and scalability for multi-agent reinforcement learning-based pedestrian models
F Martinez-Gil, M Lozano, F Fernandez
Simulation Modelling Practice and Theory 74, 117-133, 2017
192017
Calibrating a motion model based on reinforcement learning for pedestrian simulation
F Martinez-Gil, M Lozano, F Fernández
International Conference on Motion in Games, 302-313, 2012
122012
A Reinforcement Learning Approach for Multiagent Navigation.
F Martinez-Gil, F Barber, M Lozano, F Grimaldo, F Fernández
ICAART (1), 607-610, 2010
82010
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
52014
MARL-Ped+ Hitmap: Towards Improving Agent-Based Simulations with Distributed Arrays
E Rodriguez-Gutiez, F Martinez-Gil, JM Orduña, A Gonzalez-Escribano
International Conference on Algorithms and Architectures for Parallel …, 2016
12016
Phase Space Data-Driven Simulation of Elastic Materials.
C Monteagudo, M Lozano, I García-Fernández, F Martinez-Gil
CEIG, 69-73, 2016
12016
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
12008
RECONSTRUCTION OF THE AORTA GEOMETRY USING CANAL SURFACES
P Romero, S Santos, R Sebastian, F Martinez-Gil, D Serra, P Calvillo, ...
1
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
2020
MARL-Ped+ Hitmap: Aumentando la productividad de simulaciones basadas en agentes con una herramienta de arrays distribuidos
E Rodriguez-Gutiez, F Martinez-Gil, JM Orduna-Huertas, ...
Actas Jornadas SARTECO 2016 218, 97, 2020
2020
Procedural Location of Roads Using Desire Paths.
P Real, F Martínez-Gil, RJ Martínez-Durá, I García-Fernández
CEIG, 19-24, 2019
2019
Reinforcement learning in a Multi-agent Framework for Pedestrian Simulation
F Martinez-Gil
ProQuest, 2014
2014
Emergent collective behaviors in a multi-agent reinforcement learning based pedestrian simulation
F Martinez-Gil, F Fernández, M Lozano
RLDM 2013, 38, 2013
2013
MARL-Ped+ Hitmap: Aumentando la productividad de simulaciones basadas en agentes con una herramienta de arrays distribuidos
E Rodrıguez-Gutiez, F Martinez-Gil, JM Orduna-Huertas, ...
Modeling, Evaluation and Scale on artificial Pedestrians: A literature
F MARTINEZ-GIL, M LOZANO, I GARCÍA-FERNÁNDEZ, F FERNÁNDEZ
El sistema no puede realizar la operación en estos momentos. Inténtalo de nuevo más tarde.
Artículos 1–19