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Stochastic Approximations and Differential Inclusions; Part II: Applications

Citations

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Cited by:

  1. Ignacio Esponda & Demian Pouzo, 2026. "Learning and Equilibrium under Model Misspecification," Papers 2601.09891, arXiv.org.
  2. Severin Maier & Camille Castera & Peter Ochs, 2026. "Near-optimal Closed-loop Method via Lyapunov Damping," Journal of Optimization Theory and Applications, Springer, vol. 208(3), pages 1-30, March.
  3. Swenson, Brian & Murray, Ryan & Kar, Soummya, 2020. "Regular potential games," Games and Economic Behavior, Elsevier, vol. 124(C), pages 432-453.
  4. Bravo, Mario & Mertikopoulos, Panayotis, 2017. "On the robustness of learning in games with stochastically perturbed payoff observations," Games and Economic Behavior, Elsevier, vol. 103(C), pages 41-66.
  5. Andriy Zapechelnyuk, 2009. "Limit Behavior of No-regret Dynamics," Discussion Papers 21, Kyiv School of Economics.
  6. Elvira Hernández & Juan Perán, 2026. "An underlying theory of multifunctions in discrete-time set-valued dynamical systems," Journal of Optimization Theory and Applications, Springer, vol. 208(2), pages 1-18, February.
  7. Cason, Timothy N. & Friedman, Daniel & Hopkins, Ed, 2010. "Testing the TASP: An experimental investigation of learning in games with unstable equilibria," Journal of Economic Theory, Elsevier, vol. 145(6), pages 2309-2331, November.
  8. Mathieu Faure & Gregory Roth, 2010. "Stochastic Approximations of Set-Valued Dynamical Systems: Convergence with Positive Probability to an Attractor," Mathematics of Operations Research, INFORMS, vol. 35(3), pages 624-640, August.
  9. Josef Hofbauer & Sylvain Sorin & Yannick Viossat, 2009. "Time Average Replicator and Best-Reply Dynamics," Mathematics of Operations Research, INFORMS, vol. 34(2), pages 263-269, May.
  10. repec:hal:wpaper:hal-00713871 is not listed on IDEAS
  11. Bervoets, Sebastian & Faure, Mathieu, 2020. "Convergence in games with continua of equilibria," Journal of Mathematical Economics, Elsevier, vol. 90(C), pages 25-30.
  12. Giacomo Lanzani, 2025. "Dynamic Concern for Misspecification," Econometrica, Econometric Society, vol. 93(4), pages 1333-1370, July.
  13. Arunselvan Ramaswamy & Shalabh Bhatnagar, 2017. "A Generalization of the Borkar-Meyn Theorem for Stochastic Recursive Inclusions," Mathematics of Operations Research, INFORMS, vol. 42(3), pages 648-661, August.
  14. Borkar, Vivek S., 2025. "Stochastic approximation with two time scales: The general case," Stochastic Processes and their Applications, Elsevier, vol. 190(C).
  15. Bolte, Jérôme & Pauwels, Edouard, 2019. "Conservative set valued fields, automatic differentiation, stochastic gradient methods and deep learning," TSE Working Papers 19-1044, Toulouse School of Economics (TSE).
  16. van Strien, Sebastian & Sparrow, Colin, 2011. "Fictitious play in 3x3 games: Chaos and dithering behaviour," Games and Economic Behavior, Elsevier, vol. 73(1), pages 262-286, September.
  17. Bolte, Jérôme & Le, Tam & Pauwels, Edouard & Silveti-Falls, Antonio, 2022. "Nonsmooth Implicit Differentiation for Machine Learning and Optimization," TSE Working Papers 22-1314, Toulouse School of Economics (TSE).
  18. In-Koo Cho & Anna Rubinchik, 2017. "Contemplation vs. intuition: a reinforcement learning perspective," EURO Journal on Decision Processes, Springer;EURO - The Association of European Operational Research Societies, vol. 5(1), pages 141-167, November.
  19. Esponda, Ignacio & Pouzo, Demian & Yamamoto, Yuichi, 2021. "Asymptotic behavior of Bayesian learners with misspecified models," Journal of Economic Theory, Elsevier, vol. 195(C).
  20. Candogan, Ozan & Ozdaglar, Asuman & Parrilo, Pablo A., 2013. "Dynamics in near-potential games," Games and Economic Behavior, Elsevier, vol. 82(C), pages 66-90.
  21. Michel Benaïm & Josef Hofbauer & Sylvain Sorin, 2006. "Stochastic Approximations and Differential Inclusions, Part II: Applications," Mathematics of Operations Research, INFORMS, vol. 31(4), pages 673-695, November.
  22. Bervoets, Sebastian & Faure, Mathieu, 2019. "Stability in games with continua of equilibria," Journal of Economic Theory, Elsevier, vol. 179(C), pages 131-162.
  23. Benaïm, Michel & Hofbauer, Josef & Hopkins, Ed, 2009. "Learning in games with unstable equilibria," Journal of Economic Theory, Elsevier, vol. 144(4), pages 1694-1709, July.
  24. Cominetti, Roberto & Melo, Emerson & Sorin, Sylvain, 2010. "A payoff-based learning procedure and its application to traffic games," Games and Economic Behavior, Elsevier, vol. 70(1), pages 71-83, September.
  25. Ratul, Lahkar, 2011. "The dynamic instability of dispersed price equilibria," Journal of Economic Theory, Elsevier, vol. 146(5), pages 1796-1827, September.
  26. Berger, Ulrich, 2007. "Two more classes of games with the continuous-time fictitious play property," Games and Economic Behavior, Elsevier, vol. 60(2), pages 247-261, August.
  27. Kuangyu Ding & Kim-Chuan Toh, 2025. "Stochastic Bregman Subgradient Methods for Nonsmooth Nonconvex Optimization Problems," Journal of Optimization Theory and Applications, Springer, vol. 206(3), pages 1-36, September.
  28. Bolte, Jérôme & Pauwels, Edouard, 2021. "A mathematical model for automatic differentiation in machine learning," TSE Working Papers 21-1184, Toulouse School of Economics (TSE).
  29. Akimoto, Youhei & Auger, Anne & Hansen, Nikolaus, 2022. "An ODE method to prove the geometric convergence of adaptive stochastic algorithms," Stochastic Processes and their Applications, Elsevier, vol. 145(C), pages 269-307.
  30. Dileep Kalathil & Vivek S. Borkar & Rahul Jain, 2017. "Approachability in Stackelberg Stochastic Games with Vector Costs," Dynamic Games and Applications, Springer, vol. 7(3), pages 422-442, September.
  31. Edouard Pauwels, 2021. "Incremental Without Replacement Sampling in Nonconvex Optimization," Journal of Optimization Theory and Applications, Springer, vol. 190(1), pages 274-299, July.
  32. Pascal Bianchi & Walid Hachem, 2016. "Dynamical Behavior of a Stochastic Forward–Backward Algorithm Using Random Monotone Operators," Journal of Optimization Theory and Applications, Springer, vol. 171(1), pages 90-120, October.
  33. Sandholm, William H., 2015. "Population Games and Deterministic Evolutionary Dynamics," Handbook of Game Theory with Economic Applications,, Elsevier.
  34. Wouter Baar & Dario Bauso, 2022. "Mean Field Games on Prosumers," SN Operations Research Forum, Springer, vol. 3(4), pages 1-27, December.
  35. Michel Benaïm & Josef Hofbauer & Sylvain Sorin, 2012. "Perturbations of Set-Valued Dynamical Systems, with Applications to Game Theory," Dynamic Games and Applications, Springer, vol. 2(2), pages 195-205, June.
  36. Bervoets, Sebastian & Bravo, Mario & Faure, Mathieu, 2020. "Learning with minimal information in continuous games," Theoretical Economics, Econometric Society, vol. 15(4), November.
  37. Arunselvan Ramaswamy & Shalabh Bhatnagar, 2022. "Analyzing Approximate Value Iteration Algorithms," Mathematics of Operations Research, INFORMS, vol. 47(3), pages 2138-2159, August.
  38. Sylvain Sorin, 2023. "Continuous Time Learning Algorithms in Optimization and Game Theory," Dynamic Games and Applications, Springer, vol. 13(1), pages 3-24, March.
  39. Eunji Lim, 2011. "On the Convergence Rate for Stochastic Approximation in the Nonsmooth Setting," Mathematics of Operations Research, INFORMS, vol. 36(3), pages 527-537, August.
  40. Vinayaka G. Yaji & Shalabh Bhatnagar, 2020. "Stochastic Recursive Inclusions in Two Timescales with Nonadditive Iterate-Dependent Markov Noise," Mathematics of Operations Research, INFORMS, vol. 45(4), pages 1405-1444, November.
  41. Prasenjit Karmakar & Shalabh Bhatnagar, 2018. "Two Time-Scale Stochastic Approximation with Controlled Markov Noise and Off-Policy Temporal-Difference Learning," Mathematics of Operations Research, INFORMS, vol. 43(1), pages 130-151, February.
  42. Saeed Hadikhanloo & Rida Laraki & Panayotis Mertikopoulos & Sylvain Sorin, 2022. "Learning in nonatomic games, part Ⅰ: Finite action spaces and population games," Post-Print hal-03767995, HAL.
  43. Panayotis Mertikopoulos & William H. Sandholm, 2016. "Learning in Games via Reinforcement and Regularization," Mathematics of Operations Research, INFORMS, vol. 41(4), pages 1297-1324, November.
  44. Benoit Duvocelle & Panayotis Mertikopoulos & Mathias Staudigl & Dries Vermeulen, 2023. "Multiagent Online Learning in Time-Varying Games," Mathematics of Operations Research, INFORMS, vol. 48(2), pages 914-941, May.
  45. Andrés Contreras & Juan Peypouquet, 2019. "Asymptotic Equivalence of Evolution Equations Governed by Cocoercive Operators and Their Forward Discretizations," Journal of Optimization Theory and Applications, Springer, vol. 182(1), pages 30-48, July.
  46. Leslie, David S. & Collins, E.J., 2006. "Generalised weakened fictitious play," Games and Economic Behavior, Elsevier, vol. 56(2), pages 285-298, August.
  47. Drew Fudenberg & Florian Mudekereza, 2026. "Complexity and Misspecification," Papers 2602.15674, arXiv.org, revised Jun 2026.
  48. Leslie, David S. & Perkins, Steven & Xu, Zibo, 2020. "Best-response dynamics in zero-sum stochastic games," Journal of Economic Theory, Elsevier, vol. 189(C).
  49. Viossat, Yannick & Zapechelnyuk, Andriy, 2013. "No-regret dynamics and fictitious play," Journal of Economic Theory, Elsevier, vol. 148(2), pages 825-842.
  50. Jérôme Bolte & Tam Le & Edouard Pauwels & Antonio Silveti Falls, 2021. "Nonsmooth implicit differentiation for machine learning and optimization," Post-Print hal-05495397, HAL.
  51. Michel Benaïm & Mathieu Faure, 2013. "Consistency of Vanishingly Smooth Fictitious Play," Mathematics of Operations Research, INFORMS, vol. 38(3), pages 437-450, August.
  52. Michel Benaim & Olivier Raimond, 2007. "Simulated Annealing, Vertex-Reinforced Random Walks and Learning in Games," Levine's Bibliography 122247000000001702, UCLA Department of Economics.
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