Francisco Martinez-Gil

13 papers A 1C 2Journal 6Unranked 4
YearRankTypeTitle / Venue / Authors
2025 J jnl
Multi-Agent Reinforcement Learning for creating intelligent agents in social networks-oriented role playing games.
Entertain. Comput.
Francisco Martinez-Gil, Eduard Gil-Magraner
2025 A conf
Where is the Nearest EV Charging Station? Evolutionary Optimization of the Gas/charging Stations Topology.
AAMAS
Enrique Mateos-Melero, Javier Moralejo-Piñas, Ángela Durán-Pinto, Francisco Martinez-Gil, María Soriano, Fernando Fernández
2017 J jnl
Emergent behaviors and scalability for multi-agent reinforcement learning-based pedestrian models.
Simul. Model. Pract. Theory
Francisco Martinez-Gil, Miguel Lozano, Fernando Fernández
2017 J jnl
Modeling, Evaluation, and Scale on Artificial Pedestrians: A Literature Review.
ACM Comput. Surv.
Francisco Martinez-Gil, Miguel Lozano, Ignacio García-Fernández, Fernando Fernández
2016 — conf
MARL-Ped+Hitmap: Towards Improving Agent-Based Simulations with Distributed Arrays.
ICA3PP Workshops
Eduardo Rodriguez-Gutiez, Francisco Martinez-Gil, Juan Manuel Orduña, Arturo González-Escribano
2016 — conf
Phase Space Data-Driven Simulation of Elastic Materials.
CEIG
Carlos Monteagudo, Miguel Lozano, Ignacio García-Fernández, Francisco Martinez-Gil
2015 J jnl
Strategies for simulating pedestrian navigation with multiple reinforcement learning agents.
Auton. Agents Multi Agent Syst.
Francisco Martinez-Gil, Miguel Lozano, Fernando Fernández
2014 C conf
Emergent Collective Behaviors in a Multi-agent Reinforcement Learning Pedestrian Simulation: A Case Study.
MABS
Francisco Martinez-Gil, Miguel Lozano, Fernando Fernández
2014 J jnl
MARL-Ped: A multi-agent reinforcement learning based framework to simulate pedestrian groups.
Simul. Model. Pract. Theory
Francisco Martinez-Gil, Miguel Lozano, Fernando Fernández
2012 C conf
Calibrating a Motion Model Based on Reinforcement Learning for Pedestrian Simulation.
MIG
Francisco Martinez-Gil, Miguel Lozano, Fernando Fernández
2011 — conf
Multi-agent Reinforcement Learning for Simulating Pedestrian Navigation.
ALA
Francisco Martinez-Gil, Miguel Lozano, Fernando Fernández
2010 — conf
A Reinforcement Learning Approach for Multiagent Navigation.
ICAART (1)
Francisco Martinez-Gil, Fernando Barber, Miguel Lozano, Francisco Grimaldo, Fernando Fernández
2008 J jnl
Agent's actions as a classification criteria for the state space in a learning from rewards system.
J. Exp. Theor. Artif. Intell.
Francisco Martinez-Gil