Publications

• PAPERS [1] Prieto-Rumeau, T. (2003). Statistical inference for a finite optimal stopping problem with unknown transition probabilities. Test 12, No. 1, pp. 215-239.
  
  [2] Lasserre, J.B., Prieto-Rumeau, T. (2004). SDP vs LP relaxations in some performance evaluation problems. Stoch. Models 20, No. 4, pp. 439-456.

  [3] Prieto-Rumeau, T. (2004). Estimation of an optimal solution of a linear programming problem with unknown objective function. Math. Program. 101, No. 3, pp. 463-478.
  
  [4] Prieto-Rumeau, T., Hernández-Lerma, O. (2005). The Laurent series, sensitive discount and Blackwell optimality for continuous-time controlled Markov chains. Math. Methods Oper. Res. 61, No. 1, pp. 123-145.
  
  [5] Prieto-Rumeau, T., Hernández-Lerma, O. (2005). Bias and overtaking equilibria for continuous-time zero-sum Markov games. Math. Methods Oper. Res. 61, No. 3, pp. 437-454.
  
  [6] Prieto-Rumeau, T. (2005). Central limit theorem for the estimator of the value of an optimal stopping problem. Test 14, No. 1, pp. 215-237.

  [7] Prieto-Rumeau, T., Hernández-Lerma, O. (2006). Bias optimality for continuous-time controlled Markov chains. SIAM J. Control Optim. 45, No. 1, pp. 51-73.
  
  [8] Lasserre, J.B., Prieto-Rumeau, T., Zervos, M. (2006). Pricing a class of exotic options via moments and SDP relaxations. Math. Finance 16, No. 3, pp. 469-494.

  [9] Prieto-Rumeau, T. (2006). Blackwell optimality in the class of Markov policies for continuous-time controlled Markov chains. Acta Appl. Math. 92, No. 1, pp. 77-96.
  
  [10] Guo, X.P., Hernández-Lerma, O., Prieto-Rumeau, T. (2006). A survey of recent results on continuous-time Markov decision processes. Top 14, No. 2, pp. 177-261.

  [11] Prieto-Rumeau, T., Hernández-Lerma, O. (2008). Ergodic control of continuous-time Markov chains with pathwise constraints. SIAM J. Control Optim. 47, No. 4, pp. 1888-1908.

  [12] Zhu, Q.X., Prieto-Rumeau, T. (2008). Bias and overtaking optimality for continuous-time jump Markov decision processes in Polish spaces. J. Appl. Probab. 45, No. 2, pp. 417-429.

  [13] Prieto-Rumeau, T. (2008). Stochastic algorithms for the estimation of an optimal solution of a LP problem. Convergence and central limit theorem. Comm. Statist. Theory Methods 37, No. 20, pp. 3308-3318.

  [14] Vélez Ibarrola, R., Prieto-Rumeau, T. (2008). A De Finetti-type theorem for nonexchangeable finite-valued random variables. J. Math. Anal. Appl. 347, No. 2, pp. 407-415.

  [15] Prieto-Rumeau, T., Hernández-Lerma, O. (2009). Variance minimization and the overtaking optimality approach to continuous-time controlled Markov chains. Math. Methods Oper. Res. 70, No. 3, pp. 527-540.

  [16] Vélez Ibarrola, R., Prieto-Rumeau, T. (2009). De Finetti's-type results for some families of non identically distributed random variables. Electron. J. Probab. 14, pp. 72-86.

  [17] Vélez Ibarrola, R., Prieto-Rumeau, T. (2010). De Finetti-type theorems for random selection processes. Necessary and sufficient conditions. J. Math. Anal. Appl. 365, No. 1, pp. 198-209.

  [18] Prieto-Rumeau, T., Lorenzo, J.M. (2010). Approximating ergodic average reward continuous-time controlled Markov chains. IEEE Trans. Automat. Control 55, No. 1, pp. 201-207.

  [19] Prieto-Rumeau, T., Hernández-Lerma, O. (2010). The vanishing discount approach to constrained continuous time controlled Markov chains. Systems Control Lett. 59, No. 8, pp. 504-509.

  [20] Vélez Ibarrola, R., Prieto-Rumeau, T. (2011). De Finetti-type theorems for nonexchangeable 0-1 random variables. Test 20, No. 2, pp. 293-310.

  [21] Vélez Ibarrola, R., Prieto-Rumeau, T. (2011). Conditionally independent increments point processes. J. Appl. Probab. 48, No. 2, pp. 490-513.

  [22] Dufour, F., Prieto-Rumeau, T. (2012). Approximation of Markov decision processes with general state space. J. Math. Anal. Appl. 388, No. 2, pp. 1254-1267.

  [23] Prieto-Rumeau, T., Hernández-Lerma, O. (2012). Discounted continuous-time controlled Markov chains: convergence of control models. J. Appl. Probab. 49, No. 4.

  [24] Dufour, F., Prieto-Rumeau, T. (2013). Finite linear programming approximations of constrained discounted Markov decision processes. SIAM J. Control Optim. 51, pp. 1298-1324.

  [25] Dufour, F., Prieto-Rumeau, T. (2014). Stochastic approximations of constrained discounted Markov decision processes. J. Math. Anal. Appl. 413, pp. 856-879.

  [26] Dufour, F., Prieto-Rumeau, T. (2015). Approximation of average cost Markov decision processes using empirical distributions and concentration inequalities. Stochastics 87, pp. 273-307.

  [27] Vélez Ibarrola, R., Prieto-Rumeau, T. (2015). Random assignment processes: strong law of large numbers and De Finetti theorem. Test 24, pp. 136-165.

  [28] Prieto-Rumeau, T., Lorenzo, J.M. (2015). Approximation of zero-sum continuous-time Markov games under the discounted payo criterion. Top 23, pp. 799-836.

  [29] Lorenzo, J.M., Hernandez-Noriega, I., Prieto-Rumeau, T. (2015). Approximation of two-person zero-sum continuous-time Markov games with average payo criterion. Oper. Res. Lett. 43, pp. 110-116.

  [30] Dufour, F., Prieto-Rumeau, T. (2016). Conditions for the solvability of the linear programming formulation for constrained discounted Markov decision processes. Appl. Math. Opt. 74, pp. 27-51.

  [31] Prieto-Rumeau, T., Hernández-Lerma, O. (2016). Uniform ergodicity of continuous-time controlled Markov chains: a survey and new results. Ann. Oper. Res. 241, pp. 249-293.

  [32] Anselmi, J., Dufour, F., Prieto-Rumeau, T. (2016). Computable approximations for continuous-time Markov decision processes on Borel spaces based on empirical measures. J. Math. Anal. Appl. 443, pp. 1312-1361.

  [33] Jasso-Fuentes, H., Menaldi, J.L., Prieto-Rumeau, T., Robin, M. (2018). Discrete-time hybrid control in Borel spaces: average cost optimality criterion. J. Math. Anal. Appl. 462, pp. 1695-1713.

  [34] Anselmi, J., Dufour, F., Prieto-Rumeau, T. (2018). Computable approximations for average Markov decision processes in continuous time. J. Appl. Probab. 55, pp. 571-592.

  [35] Dufour, F., Prieto-Rumeau, T. (2019). Approximation of discounted minimax Markov control problems and zero-sum Markov games using Hausdorff and Wasserstein distances. Dyn. Games Appl. 9, pp. 68-102.

  [36] Jasso-Fuentes, H., Menaldi, J.L., Prieto-Rumeau, T. (2020). Discrete time hybrid control in Borel spaces. Appl. Math. Opt. 81, pp. 409-441.

  [37] Jasso-Fuentes, H., Menaldi, J.L., Prieto-Rumeau, T. (2020). Discrete-time control with non-constant discount factor. Math. Methods Oper. Res. 92, pp. 377-399.

  [38] Dufour, F., Prieto-Rumeau, T. (2022). Maximizing the probability of visiting a set infinitely often for a countable state space Markov decision process. J. Math. Anal. Appl. 505, paper 125639, 21 pp.

  [39] Dufour, F., Prieto-Rumeau, T. (2022). Stationary Markov Nash equilibria for nonzero-sum constrained ARAT Markov games. SIAM J. Control Optim. 60, pp. 945-967.

  [40] Dufour, F., Prieto-Rumeau, T. (2024). Absorbing Markov decision processes. ESAIM - Control Optim. Calc. Var. 30, 5.

  [41] Dufour, F., Prieto-Rumeau, T. (2024). Nash equilibria for total expected reward absorbing Markov games: the constrained and unconstrained cases. Appl. Math. Opt. 89, 34.

  [42] Dufour, F., Prieto-Rumeau, T. (2024). Maximizing the probability of visiting a set infinitely often for a Markov decision process with Borel state and actions spaces. J. Appl. Probab. 61, In Press.

  [43] Jasso-Fuentes, H., Menaldi, J.L., Prieto-Rumeau, T. (2024). Recent results on discrete-time hybrid control models with general state and action spaces. Pure Appl. Func. Anal. 9, pp. 675-704.

• CONFERENCE PAPERS [1] Prieto-Rumeau, T. (2003). Stochastic simplex algorithm for a linear programming problem with unknown objective function. Proceedings of the Conference EYSM'03, eds: Fournier, B., Fürrer, R., Gsponer, T., Restle, E.M., ISBN 3-908152-17-8, pp. 113-122.
  
  [2] Prieto-Rumeau, T., Hernández-Lerma, O. (2010). Policy iteration and finite approximations to discounted continuous-time controlled Markov chains. Modern Trends in Controlled Stochastic Processes: Theory and Applications, ed.: Piunovskiy, A.B., ISBN 1-905-986-30-0, Luniver Press, pp. 84-101.

  [3] Dufour, F., Prieto-Rumeau, T. (2012). Approximation of infinite horizon discounted cost Markov decision processes. Optimization, Control, and Applications of Stochastic Systems. In Honor of Onésimo Hernández-Lerma, eds.: Hernández-Hernández, D., Minjárez-Sosa, J.A., ISBN 978-0-8176-8336-8, Birkhäuser, pp. 59-76.

  [4] Dufour, F., Prieto-Rumeau, T. (2015). Solving the average cost optimality equation for unichain Markov decision processes: a linear programming approach. Modern Trends in Controlled Stochastic Processes: Theory and Applications, Volume II, ed.: Piunovskiy, A.B., ISBN 1-905-986-45-9, Luniver Press, pp. 32-46.

  [5] Dufour, F., Prieto-Rumeau, T. (2019). Numerical approximations for discounted continuous time Markov decision processes. Modeling, Stochastic Control, Optimization, and Applications, eds.: Yin, G., Zhang, Q., ISBN 978-3-030-25497-1, Springer, pp. 147-171.

• BOOKS [1] Prieto-Rumeau, T., Hernández-Lerma, O. (2012). Selected Topics on Continuous-Time Controlled Markov Chains and Markov Games. Advanced Texts in Mathematics. Imperial College Press, London.

  [2] Vélez Ibarrola, R., Prieto-Rumeau, T. (2013). Procesos Estocásticos. Editorial UNED, in Spanish.