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Francisco Martinez-Gil
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2010 – 2019
- 2019
- [c7]Pablo Real, Francisco Martínez-Gil, Rafael J. Martínez-Durá, Ignacio García-Fernández:
Procedural Location of Roads Using Desire Paths. CEIG 2019: 19-24 - 2017
- [j5]Francisco Martinez-Gil, Miguel Lozano, Ignacio García-Fernández, Fernando Fernández:
Modeling, Evaluation, and Scale on Artificial Pedestrians: A Literature Review. ACM Comput. Surv. 50(5): 72:1-72:35 (2017) - [j4]Francisco Martinez-Gil, Miguel Lozano, Fernando Fernández:
Emergent behaviors and scalability for multi-agent reinforcement learning-based pedestrian models. Simul. Model. Pract. Theory 74: 117-133 (2017) - 2016
- [c6]Carlos Monteagudo, Miguel Lozano, Ignacio García-Fernández, Francisco Martinez-Gil:
Phase Space Data-Driven Simulation of Elastic Materials. CEIG 2016: 69-73 - [c5]Eduardo Rodriguez-Gutiez, Francisco Martinez-Gil, Juan Manuel Orduña, Arturo González-Escribano:
MARL-Ped+Hitmap: Towards Improving Agent-Based Simulations with Distributed Arrays. ICA3PP Workshops 2016: 212-225 - 2015
- [j3]Francisco Martinez-Gil, Miguel Lozano, Fernando Fernández:
Strategies for simulating pedestrian navigation with multiple reinforcement learning agents. Auton. Agents Multi Agent Syst. 29(1): 98-130 (2015) - 2014
- [j2]Francisco Martinez-Gil, Miguel Lozano, Fernando Fernández:
MARL-Ped: A multi-agent reinforcement learning based framework to simulate pedestrian groups. Simul. Model. Pract. Theory 47: 259-275 (2014) - [c4]Francisco Martinez-Gil, Miguel Lozano, Fernando Fernández:
Emergent Collective Behaviors in a Multi-agent Reinforcement Learning Pedestrian Simulation: A Case Study. MABS 2014: 228-238 - 2012
- [c3]Francisco Martinez-Gil, Miguel Lozano, Fernando Fernández:
Calibrating a Motion Model Based on Reinforcement Learning for Pedestrian Simulation. MIG 2012: 302-313 - 2011
- [c2]Francisco Martinez-Gil, Miguel Lozano, Fernando Fernández:
Multi-agent Reinforcement Learning for Simulating Pedestrian Navigation. ALA 2011: 54-69 - 2010
- [c1]Francisco Martinez-Gil, Fernando Barber, Miguel Lozano, Francisco Grimaldo, Fernando Fernández:
A Reinforcement Learning Approach for Multiagent Navigation. ICAART (1) 2010: 607-610
2000 – 2009
- 2008
- [j1]Francisco Martinez-Gil:
Agent's actions as a classification criteria for the state space in a learning from rewards system. J. Exp. Theor. Artif. Intell. 20(4): 269-276 (2008)
Coauthor Index
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