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Mario Bravo
Mario Bravo
Faculty of Engineering and Sciences, Universidad Adolfo Ibáñez
Verified email at usach.cl
Title
Cited by
Cited by
Year
Bandit learning in concave N-person games
M Bravo, D Leslie, P Mertikopoulos
Advances in Neural Information Processing Systems 31, 2018
1342018
An integrated behavioral model of the land-use and transport systems with network congestion and location externalities
M Bravo, L Briceño, R Cominetti, CE Cortés, F Martínez
Transportation Research Part B: Methodological 44 (4), 584-596, 2010
702010
On the robustness of learning in games with stochastically perturbed payoff observations
M Bravo, P Mertikopoulos
Games and Economic Behavior 103, 41-66, 2017
492017
Learning with minimal information in continuous games
S Bervoets, M Bravo, M Faure
Theoretical Economics 15 (4), 1471-1508, 2020
252020
Rates of convergence for inexact Krasnosel’skii–Mann iterations in Banach spaces
M Bravo, R Cominetti, M Pavez-Signé
Mathematical Programming 175, 241-262, 2019
212019
Sharp convergence rates for averaged nonexpansive maps
M Bravo, R Cominetti
Israel Journal of Mathematics 227 (1), 163-188, 2018
202018
Learning and convergence to Nash in games with continuous action sets
S Bervoets, M Bravo, M Faure
Working paper, 2016
152016
An adjusted payoff-based procedure for normal form games
M Bravo
Mathematics of Operations Research 41 (4), 1469-1483, 2016
122016
Reinforcement learning with restrictions on the action set
M Bravo, M Faure
SIAM Journal on Control and Optimization 53 (1), 287-312, 2015
122015
An adjusted payoff-based procedure for normal form games
M Bravo
arXiv preprint arXiv:1106.5596, 2011
92011
Stochastic fixed-point iterations for nonexpansive maps: Convergence and error bounds
M Bravo, R Cominetti
SIAM Journal on Control and Optimization 62 (1), 191-219, 2024
52024
Universal bounds for fixed point iterations via optimal transport metrics
M Bravo, T Champion, R Cominetti
arXiv preprint arXiv:2108.00300, 2021
42021
Stochastic Halpern iteration in normed spaces and applications to reinforcement learning
M Bravo, JP Contreras
arXiv preprint arXiv:2403.12338, 2024
12024
Universal bounds for fixed point iterations via optimal transport metrics
T Champion, M Bravo, R Cominetti
2021
Bandit learning in concave N-player games
M Bravo, DS Leslie, P Mertikopoulos
2018
Learning and Convergence to Nash in Network Games with Continuous Action Set Preliminary Draft
S Bervoets, M Bravo, M Faure
2016
An Integrated Behavioral Model of Land Use and Transport System: a Hyper-Network Equilibrium Approach
M Bravo, L Briceno, R Cominetti, CE Cortés, FJ Martinez
11th World Conference on Transport ResearchWorld Conference on Transport …, 2007
2007
Optimization and Control Optimisation et contrôle (Org: Luis Briceno Arias (Universidad Técnica Federico Santa Marıa) and/et Maria Soledad Aronna (Fundaçao Getulio Vargas))
M BRAVO
Working Papers/Documents de travail
M Bravo, M Faure
THE HYPER-NETWORK EQUILIBRIUM APPROACH FOR THE LAND USE AND TRANSPORT INTEGRATED MODEL: THE CASE WITH EXTERNALITIES
M Bravo, L Briceño, R Cominetti, CE Cortés, F Martínez
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