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Julio B. Clempner
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2020 – today
- 2024
- [b1]Julio B. Clempner, Alexander S. Poznyak
:
Optimization and Games for Controllable Markov Chains - Numerical Methods with Application to Finance and Engineering. Springer 2024, ISBN 978-3-031-43574-4, pp. 1-327 - [j68]Julio B. Clempner
Learning attack-defense response in continuous-time discrete-states Stackelberg Security Markov games. J. Exp. Theor. Artif. Intell. 36(7): 1239-1260 (2024) - [j67]Julio B. Clempner:
Revealing perceived individuals' self-interest. J. Oper. Res. Soc. 75(2): 336-345 (2024) - 2023
- [j66]Julio B. Clempner
A Bayesian reinforcement learning approach in markov games for computing near-optimal policies. Ann. Math. Artif. Intell. 91(5): 675-690 (2023) - [j65]Julio B. Clempner, Alexander S. Poznyak:
Computing a mechanism for a Bayesian and partially observable Markov approach. Int. J. Appl. Math. Comput. Sci. 33(3) (2023) - [j64]Julio B. Clempner
Computing fortification games in a tri-level Stackelberg Markov chains approach. Eng. Appl. Artif. Intell. 121: 105979 (2023) - [j63]Julio B. Clempner
A tri-level approach for computing Stackelberg Markov game equilibrium: Computational analysis. J. Comput. Sci. 68: 101995 (2023) - 2022
- [j62]Julio B. Clempner
Learning machiavellian strategies for manipulation in Stackelberg security games. Ann. Math. Artif. Intell. 90(4): 373-395 (2022) - [j61]Julio B. Clempner
A Lyapunov approach for stable reinforcement learning. Comput. Appl. Math. 41(6) (2022) - [j60]Julio B. Clempner:
Reveling misleading information for defenders and attackers in repeated Stackelberg Security Games. Eng. Appl. Artif. Intell. 110: 104703 (2022) - [j59]Julio B. Clempner:
A Manipulation Game Based on Machiavellian Strategies. IGTR 24(2): 2150015:1-2150015:28 (2022) - [j58]Julio B. Clempner:
Algorithmic-gradient approach for the Price of Anarchy and Stability for incomplete information. J. Comput. Sci. 60: 101589 (2022) - 2021
- [j57]Julio B. Clempner
A Markovian Stackelberg game approach for computing an optimal dynamic mechanism. Comput. Appl. Math. 40(6) (2021) - [j56]Cesar U. Solis
Robust integral sliding mode controller for optimisation of measurable cost functions with constraints. Int. J. Control 94(6): 1651-1663 (2021) - [j55]Julio B. Clempner
A Proximal/Gradient Approach for Computing the Nash Equilibrium in Controllable Markov Games. J. Optim. Theory Appl. 188(3): 847-862 (2021) - [j54]Julio B. Clempner
Solving the cost to go with time penalization using the Lagrange optimization approach. Soft Comput. 25(6): 4191-4199 (2021) - 2020
- [j53]Kristal K. Trejo, Julio B. Clempner, Alexander S. Poznyak:
Computing the Nash Bargaining Solution for Multiple Players in Discrete-Time Markov Chains Games. Cybern. Syst. 51(1): 1-26 (2020) - [j52]Julio B. Clempner
Shaping Emotions in Negotiation: a Nash Bargaining Solution. Cogn. Comput. 12(4): 720-735 (2020) - [j51]Román Aragon-Gómez, Julio B. Clempner:
Traffic-signal control reinforcement learning approach for continuous-time Markov games. Eng. Appl. Artif. Intell. 89: 103415 (2020) - [j50]Julio B. Clempner, Alexander S. Poznyak:
A nucleus for Bayesian Partially Observable Markov Games: Joint observer and mechanism design. Eng. Appl. Artif. Intell. 95: 103876 (2020) - [j49]Julio B. Clempner
Finding the Strong Nash Equilibrium: Computation, Existence and Characterization for Markov Games. J. Optim. Theory Appl. 186(3): 1029-1052 (2020) - [j48]Guillermo Alcantara-Jiménez, Julio B. Clempner:
Repeated Stackelberg security games: Learning with incomplete state information. Reliab. Eng. Syst. Saf. 195: 106695 (2020)
2010 – 2019
- 2019
- [j47]Cesar U. Solis
Robust Extremum Seeking for a Second Order Uncertain Plant Using a Sliding Mode Controller. Int. J. Appl. Math. Comput. Sci. 29(4): 703-712 (2019) - [j46]Julio B. Clempner, Alexander S. Poznyak:
Observer and control design in partially observable finite Markov chains. Autom. 110 (2019) - [j45]Julio B. Clempner:
A team formation method based on a Markov chains games approach. Cybern. Syst. 50(5): 417-443 (2019) - [j44]Silvia E. Albarran, Julio B. Clempner:
A Stackelberg security Markov game based on partial information for strategic decision making against unexpected attacks. Eng. Appl. Artif. Intell. 81: 408-419 (2019) - [j43]Mauricio García-Galicia, Alin A. Carsteanu
Continuous-time reinforcement learning approach for portfolio management with time penalization. Expert Syst. Appl. 129: 27-36 (2019) - [j42]Mauricio García-Galicia, Alin A. Carsteanu
Continuous-time mean variance portfolio with transaction costs: a proximal approach involving time penalization. Int. J. Gen. Syst. 48(2): 91-111 (2019) - [j41]Cesar U. Solis
Continuous-time gradient-like descent algorithm for constrained convex unknown functions: Penalty method application. J. Comput. Appl. Math. 355: 268-282 (2019) - [j40]César U. S. Solis
Handling a Kullback-Leibler divergence random walk for scheduling effective patrol strategies in Stackelberg security games. Kybernetika 55(4): 618-640 (2019) - [j39]Rodrigo Castillo González, Julio B. Clempner, Alexander S. Poznyak:
Solving traffic queues at controlled-signalized intersections in continuous-time Markov games. Math. Comput. Simul. 166: 283-297 (2019) - [j38]Erick Asiain
Controller exploitation-exploration reinforcement learning architecture for computing near-optimal policies. Soft Comput. 23(11): 3591-3604 (2019) - [c8]Cesar U. Solis, Julio B. Clempner, Alexander S. Poznyak:
DC Motor Control based on Robust run-time Optimization Algorithm. CCE 2019: 1-5 - 2018
- [j37]Julio B. Clempner:
Computing multiobjective Markov chains handled by the extraproximal method. Ann. Oper. Res. 271(2): 469-486 (2018) - [j36]Daniel Guerrero, Alin A. Carsteanu
Solving Stackelberg security Markov games employing the bargaining Nash approach: Convergence analysis. Comput. Secur. 74: 240-257 (2018) - [j35]Mireya Salgado, Julio B. Clempner:
Measuring the emotional state among interacting agents: A game theory approach using reinforcement learning. Expert Syst. Appl. 97: 266-275 (2018) - [j34]Julio B. Clempner:
On Lyapunov Game Theory Equilibrium: Static and Dynamic Approaches. IGTR 20(2): 1750033:1-1750033:14 (2018) - [j33]Erick Asiain
A Reinforcement Learning Approach for Solving the Mean Variance Customer Portfolio in Partially Observable Models. Int. J. Artif. Intell. Tools 27(8): 1850034:1-1850034:30 (2018) - [j32]Julio B. Clempner
Using the Manhattan distance for computing the multiobjective Markov chains problem. Int. J. Comput. Math. 95(11): 2269-2286 (2018) - [j31]Julio B. Clempner
A continuous-time Markov Stackelberg security game approach for reasoning about real patrol strategies. Int. J. Control 91(11): 2494-2510 (2018) - [j30]Julio B. Clempner
A Tikhonov regularized penalty function approach for solving polylinear programming problems. J. Comput. Appl. Math. 328: 267-286 (2018) - [j29]Kristal K. Trejo, Julio B. Clempner, Alexander S. Poznyak:
Adapting attackers and defenders patrolling strategies: A reinforcement learning approach for Stackelberg security games. J. Comput. Syst. Sci. 95: 35-54 (2018) - [j28]Julio B. Clempner:
Strategic Manipulation Approach for Solving Negotiated Transfer Pricing Problem. J. Optim. Theory Appl. 178(1): 304-316 (2018) - [c7]Cesar U. Solis, Julio B. Clempner, Alexander S. Poznyak:
Continuous-Time Extremum Seeking with Function Measurements Disturbed by Stochastic Noise: A Synchronous Detection Approach. CCE 2018: 1-5 - [c6]Cesar U. Solis, Julio B. Clempner, Alexander S. Poznyak:
Constrained Extremum Seeking with Function Measurements Disturbed by Stochastic Noise. CCE 2018: 1-4 - 2017
- [j27]Julio B. Clempner, Alexander S. Poznyak:
Negotiating transfer pricing using the Nash bargaining solution. Int. J. Appl. Math. Comput. Sci. 27(4): 853-864 (2017) - [j26]Julio B. Clempner, Alexander S. Poznyak:
Multiobjective Markov chains optimization problem with strong Pareto frontier: Principles of decision making. Expert Syst. Appl. 68: 123-135 (2017) - [j25]Julio B. Clempner:
A Game Theory Model for Manipulation Based on Machiavellianism: Moral and Ethical Behavior. J. Artif. Soc. Soc. Simul. 20(2) (2017) - [j24]Julio B. Clempner:
Classical workflow nets and workflow nets with reset arcs: using Lyapunov stability for soundness verification. J. Exp. Theor. Artif. Intell. 29(1): 43-57 (2017) - [j23]Julio B. Clempner, Alexander S. Poznyak:
Using the extraproximal method for computing the shortest-path mixed Lyapunov equilibrium in Stackelberg security games. Math. Comput. Simul. 138: 14-30 (2017) - [j22]Cesar U. Solis
Fast Terminal Sliding-Mode Control With an Integral Filter Applied to a Van Der Pol Oscillator. IEEE Trans. Ind. Electron. 64(7): 5622-5628 (2017) - [c5]Daniel Guerrero, Alin A. Carsteanu, Rocio Huerta
An iterative method for solving stackelberg security games: A Markov games approach. CCE 2017: 1-6 - 2016
- [j21]Julio B. Clempner, Alexander S. Poznyak:
Conforming coalitions in Markov Stackelberg security games: Setting max cooperative defenders vs. non-cooperative attackers. Appl. Soft Comput. 47: 1-11 (2016) - [j20]Julio B. Clempner:
Necessary and sufficient Karush-Kuhn-Tucker conditions for multiobjective Markov chains optimality. Autom. 71: 135-142 (2016) - [j19]Cesar U. Solis
Modeling Multileader-Follower Noncooperative Stackelberg Games. Cybern. Syst. 47(8): 650-673 (2016) - [j18]Julio B. Clempner, Alexander S. Poznyak:
Convergence analysis for pure stationary strategies in repeated potential games: Nash, Lyapunov and correlated equilibria. Expert Syst. Appl. 46: 474-484 (2016) - [j17]Kristal K. Trejo, Julio B. Clempner, Alexander S. Poznyak:
An optimal strong equilibrium solution for cooperative multi-leader-follower Stackelberg Markov chains games. Kybernetika 52(2): 258-279 (2016) - [j16]Julio B. Clempner, Alexander S. Poznyak:
Solving the Pareto front for multiobjective Markov chains using the minimum Euclidean distance gradient-based optimization method. Math. Comput. Simul. 119: 142-160 (2016) - [c4]Kristal K. Trejo, Julio B. Clempner, Alexander S. Poznyak:
Adapting strategies to dynamic environments in controllable stackelberg security games. CDC 2016: 5484-5489 - 2015
- [j15]Julio B. Clempner, Alexander S. Poznyak:
Computing the strong Nash equilibrium for Markov chains games. Appl. Math. Comput. 265: 911-927 (2015) - [j14]Kristal K. Trejo, Julio B. Clempner, Alexander S. Poznyak:
Computing the Stackelberg/Nash Equilibria Using the Extraproximal Method: Convergence Analysis and Implementation Details for Markov Chains Games. Int. J. Appl. Math. Comput. Sci. 25(2): 337-351 (2015) - [j13]Kristal K. Trejo, Julio B. Clempner, Alexander S. Poznyak:
A Stackelberg security game with random strategies based on the extraproximal theoretic approach. Eng. Appl. Artif. Intell. 37: 145-153 (2015) - [j12]Julio B. Clempner, Alexander S. Poznyak:
Modeling the multi-traffic signal-control synchronization: A Markov chains game theory approach. Eng. Appl. Artif. Intell. 43: 147-156 (2015) - [j11]Emma M. Sánchez, Julio B. Clempner, Alexander S. Poznyak:
A priori-knowledge/actor-critic reinforcement learning architecture for computing the mean-variance customer portfolio: The case of bank marketing campaigns. Eng. Appl. Artif. Intell. 46: 82-92 (2015) - [j10]Julio B. Clempner, Alexander S. Poznyak:
Stackelberg security games: Computing the shortest-path equilibrium. Expert Syst. Appl. 42(8): 3967-3979 (2015) - [j9]Emma M. Sánchez, Julio B. Clempner, Alexander S. Poznyak:
Solving the mean-variance customer portfolio in Markov chains using iterated quadratic/Lagrange programming: A credit-card customer limits approach. Expert Syst. Appl. 42(12): 5315-5327 (2015) - [j8]Julio B. Clempner:
Setting Cournot Versus Lyapunov Games Stability Conditions and Equilibrium Point Properties. IGTR 17(4): 1550011:1-1550011:10 (2015) - [c3]Rodrigo G. Castillo, Julio B. Clempner, Alexander S. Poznyak:
Solving the multi-traffic signal-control problem for a class of continuous-time markov games. CCE 2015: 1-5 - [c2]Kristal K. Trejo, Julio B. Clempner, Alexander S. Poznyak:
Computing the Lp-strong nash equilibrium looking for cooperative stability in multiple agents markov games. CCE 2015: 1-6 - 2014
- [j7]Julio B. Clempner:
An analytical method for well-formed workflow/Petri net verification of classical soundness. Int. J. Appl. Math. Comput. Sci. 24(4): 931-939 (2014) - [j6]Julio B. Clempner:
Verifying soundness of business processes: A decision process Petri nets approach. Expert Syst. Appl. 41(11): 5030-5040 (2014) - 2013
- [c1]Julio B. Clempner, Alexander S. Poznyak:
Analysis of best-reply strategies in repeated finite Markov chains games. CDC 2013: 568-573 - 2011
- [j5]Julio B. Clempner, Alexander S. Poznyak:
Convergence method, properties and computational complexity for Lyapunov games. Int. J. Appl. Math. Comput. Sci. 21(2): 349-361 (2011) - 2010
- [j4]Julio B. Clempner:
A hierarchical decomposition of decision process Petri nets for modeling complex systems. Int. J. Appl. Math. Comput. Sci. 20(2): 349-366 (2010) - [j3]Julio B. Clempner:
A Pattern Model for Assessing Work Competencies Using Petri Nets. Int. J. Comput. Sci. Appl. 7(4): 50-77 (2010)
2000 – 2009
- 2009
- [j2]Julio B. Clempner:
A Shortest-Path Lyapunov Approach for Forward Decision Processes. Int. J. Comput. Games Technol. 2009: 162450:1-162450:12 (2009) - 2005
- [j1]Zvi Retchkiman Königsberg, Julio B. Clempner:
Decision Process Petri Nets: Analysis and Optimization. Neural Parallel Sci. Comput. 13: 245-264 (2005)
Coauthor Index
Alex Poznyak
aka: Alexander S. Poznyak
aka: Alexander S. Poznyak
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