Publications

2025

Rollout, Policy Iteration, and Distributed Reinforcement Learning [Book Review]

D. P. Bertsekas; M. Kamgarpour 

IEEE Control Systems. 2025. Vol. 45, num. 6, p. 134 – 136. DOI : 10.1109/mcs.2025.3615016.

Deep learning-driven MRI for accurate brain volumetry in murine models of neurodegenerative diseases

A. Doelemeyer; S. Vaishampayan; S. Zurbruegg; F. Morvan; G. Locatelli et al. 

Frontiers in Neuroscience. 2025. Vol. 19. DOI : 10.3389/fnins.2025.1632169.

Learning to Assemble with Alternative Plans

Z. Wang; W. Liu; J. Wang; G. Vallat; F. Shi et al. 

ACM Transactions on Graphics. 2025. Vol. 44, num. 4, p. 1 – 16. DOI : 10.1145/3730824.

Nash equilibria in scalar discrete-time linear quadratic games

G. Salizzoni; R. Ouhamma; M. Kamgarpour 

2025. 2025 European Control Conference (ECC), Thessaloniki, Greece, 2025-06-24 – 2025-06-27. p. 2416 – 2421. DOI : 10.23919/ecc65951.2025.11187226.

Efficient Preference-Based Reinforcement Learning: Randomized Exploration Meets Experimental Design

A. Schlaginhaufen; R. Ouhamma; M. Kamgarpour 

2025

A learning-based approach to stochastic optimal control under reach-avoid constraint

T. Ni; M. Kamgarpour 

2025. 28th ACM International Conference on Hybrid Systems: Computation and Control (HSCC 2025)., Irvine CA USA, 2025-05-06 – 2025-05-09. p. 1 – 8. DOI : 10.1145/3716863.3718055.

Safe optimization with grey-box information: Application to composites autoclave processing improvement on the fly

M. A. Roohi; M. Ramezankhani; M. Kamgarpour; A. S. Milani 

Composites Part C: Open Access. 2025. Vol. 16, p. 100560. DOI : 10.1016/j.jcomc.2025.100560.

On the approximation of vector-valued functions by volume sampling

D. Kressner; T. Ni; A. Uschmajew 

Journal of Complexity. 2025. Vol. 86, p. 101887. DOI : 10.1016/j.jco.2024.101887.

Chance-Constrained Linear Quadratic Gaussian Games for Multi-Robot Interaction Under Uncertainty

K. Ren; G. Salizzoni; M. E. Gürsoy; M. Kamgarpour 

IEEE Control Systems Letters. 2025.  p. 1 – 1. DOI : 10.1109/lcsys.2025.3588090.

On the Convergence of Gradient Descent in Scalar Two-Agent Infinite-Horizon LQ Games

G. Salizzoni; M. Kamgarpour 

IEEE Control Systems Letters. 2025.  p. 1 – 1. DOI : 10.1109/lcsys.2025.3574107.

2024

Convergence of a model-free entropy-regularized inverse reinforcement learning algorithm

T. Renard; A. Schlaginhaufen; T. Ni; M. Kamgarpour 

2024. 63rd IEEE Conference on Decision and Control, Milan, Italy, 2024-12-16 – 2024-12-19. p. 8258 – 8263. DOI : 10.1109/CDC56724.2024.10886001.

Aircraft Trajectory Planning for Climate Hotspot Avoidance Considering Air Traffic Complexity: A Constrained Multi-Agent Reinforcement Learning Approach

F. Baneshi; M. Cerezo Magaña; M. Soler; T. Ni; M. Kamgarpour 

2024. SESAR Innovation Days 2024, Rome, 2024-11-12 – 2024-11-15.

Recursively Feasible Chance-Constrained Model Predictive Control Under Gaussian Mixture Model Uncertainty

K. Ren; C. Chen; H. Sung; H. Ahn; I. M. Mitchell et al. 

IEEE Transactions on Control Systems Technology. 2024.  p. 1 – 14. DOI : 10.1109/TCST.2024.3477089.

Learning to bid in forward electricity markets using a no-regret algorithm

A. Getaneh Abate; D. Majdi; J. Kazempour; M. Kamgarpour 

Electric Power Systems Research. 2024. Vol. 234, p. 110693. DOI : 10.1016/j.epsr.2024.110693.

A Distributed Augmenting Path Approach for the Bottleneck Assignment Problem

M. Khoo; T. A. Wood; C. Manzie; I. Shames 

Ieee Transactions On Automatic Control. 2024. Vol. 69, num. 2, p. 1210 – 1217. DOI : 10.1109/TAC.2023.3279336.

Payoff-Based Learning of Nash Equilibria in Merely Monotone Games

T. Tatarenko; M. Kamgarpour 

IEEE Transactions on Control of Network Systems. 2024.  p. 1 – 12. DOI : 10.1109/TCNS.2024.3355035.

Multi-Agent Learning in Contextual Games under Unknown Constraints

M. Kamgarpour; A. M. Maddux 

2024. 27th International Conference on Artificial Intelligence and Statistics, Palau de Congressos, Valencia, Spain, 2024-05-02 – 2024-05-04.

2023

Reinforcement learning for scaffold-free construction of spanning-structures

G. Vallat; J. Wang; A. M. Maddux; M. Kamgarpour; S. Parascho 

2023. 8th ACM Symposium on Computational Fabrication (SCF), New York, NY, OCT 08-10, 2023. DOI : 10.1145/3623263.3623359.

Certification of Bottleneck Task Assignment With Shortest Path Criteria

M. Kamgarpour; T. A. Wood 

IEEE Robotics and Automation. 2023. Vol. 8, p. 4545 – 4552. DOI : 10.1109/LRA.2023.3286815.

Provable Convergence Guarantees for Constrained Inverse Reinforcement Learning

T. Renard 

2023.

Constrained Inverse Reinforcement Learning: Challenges and Solutions for Real World Implementation

P. Chassagne 

2023.

Learning to make mixed-integer robot motion planning easy

T. Lewko 

2023.

Multi-agent Reinforcement Learning for Assembly of a Spanning Structure

G. Vallat 

2023.

Identifiability and Generalizability in Constrained Inverse Reinforcement Learning

A. Schlaginhaufen; M. Kamgarpour 

2023. International Conference on Machine Learning, Honolulu, Hawaï, July 23-29, 2023.

Multi-robot task allocation for safe planning against stochastic hazard dynamics

M. Kamgarpour; D. Tihanyi; Y. Lu; O. Karaca 

2023. European Control Conference (ECC), Bucharest, Romania, June 13-16, 2023. DOI : 10.23919/ECC57647.2023.10178126.

Safe Zeroth-Order Convex Optimization Using Quadratic Local Approximations

B. Guo; Y. Jiang; M. Kamgarpour; G. Ferrari Trecate 

2023. 21st European Control Conference – ECC2023, Bucharest, Romania, June 13-16, 2023. DOI : 10.23919/ECC57647.2023.10178374.

Data-Driven Behaviour Estimation in Parametric Games

A. M. Maddux; N. Pagan; G. Belgioioso; F. Doerfler 

2023. 22nd World Congress of the International Federation of Automatic Control (IFAC), Yokohama, JAPAN, JUL 09-14, 2023. p. 9330 – 9335. DOI : 10.1016/j.ifacol.2023.10.220.

2022

Enabling inter-area reserve exchange through stable benefit allocation mechanisms *

O. Karaca; S. Delikaraoglou; G. Hug; M. Kamgarpour 

Omega-International Journal Of Management Science. 2022. Vol. 113, p. 102711. DOI : 10.1016/j.omega.2022.102711.

Iterative Graph Deformation for Aircraft Trajectory Planning Considering Ensemble Forecasting of Thunderstorms

E. Andres; D. González-Arribas; M. Soler; M. Kamgarpour; M. Sanjurjo-Rivo et al. 

SSRN Electronic Journal. 2022. DOI : 10.2139/ssrn.4215235.

Optimal Task Assignment and Collision Avoidance for Mobile Robots

D. Hollosi 

2022.

Coordination and control of a group of ground robots

P. Chassagne 

2022.

Chance-Constrained Trajectory Planning With Multimodal Environmental Uncertainty

K. Ren; H. Ahn; M. Kamgarpour 

Ieee Control Systems Letters. 2022. Vol. 7, p. 13 – 18. DOI : 10.1109/LCSYS.2022.3186269.

A greedy and distributable approach to the Lexicographic Bottleneck Assignment Problem with conditions on exactness

M. Khoo; T. A. Wood; C. Manzie; I. Shames 

Automatica. 2022. Vol. 140, p. 110240. DOI : 10.1016/j.automatica.2022.110240.

Efficient Model-based Multi-agent Reinforcement Learning via Optimistic Equilibrium Computation

P. G. Sessa; M. Kamgarpour; A. Krause 

2022. 38th International Conference on Machine Learning (ICML), Baltimore, MD, Jul 17-23, 2022. p. 19580 – 19597.

Safe Motion Planning against Multimodal Distributions Based on a Scenario Approach

H. Ahn; C. Chen; I. Mitchell; M. Kamgarpour 

IEEE Control Systems Letters. 2022. Vol. 6, p. 1142 – 1147. DOI : 10.1109/LCSYS.2021.3089641.

2021

Online Submodular Resource Allocation with Applications to Rebalancing Shared Mobility Systems

P. G. Sessa; I. Bogunovic; A. Krause; M. Kamgarpour 

2021. International Conference on Machine Learning, 2021-07-01. p. 9455 – 9464.

Fast Projection Onto Convex Smooth Constraints

I. Usmanova; M. Kamgarpour; A. Krause; K. Levy 

2021. International Conference on Machine Learning, 2021-07-01. p. 10476 – 10486.

Sample Complexity of Linear Quadratic Gaussian (LQG) Control for Output Feedback Systems

Y. Zheng; L. Furieri; M. Kamgarpour; N. Li 

2021. Learning for Dynamics and Control, 2021-05-29. p. 559 – 570.

Multi-robot task allocation for safe planning against stochastic hazard dynamics

D. Tihanyi; Y. Lu; O. Karaca; M. Kamgarpour 

2021

RRT*-Based Algorithm for Trajectory Planning Considering Probabilistic Weather Forecasts

E. Andrés; M. Kamgarpour; M. Soler; M. Sanjurjo-Rivo; D. González-Arribas 

Lecture Notes in Electrical Engineering. 2021. Vol. 731 LNEE, p. 245 – 258. DOI : 10.1007/978-981-33-4669-7_14.

Bandit Online Learning of Nash Equilibria in Monotone Games

T. Tatarenko; M. Kamgarpour 

2021

Trajectory planning under environmental uncertainty with finite-sample safety guarantees

V. Lefkopoulos; M. Kamgarpour 

Automatica. 2021. Vol. 131, p. 109754. DOI : 10.1016/j.automatica.2021.109754.

Performance guarantees of forward and reverse greedy algorithms for minimizing nonsupermodular nonsubmodular functions on a matroid

O. Karaca; D. Tihanyi; M. Kamgarpour 

Operations Research Letters. 2021. Vol. 49, num. 6, p. 855 – 861. DOI : 10.1016/j.orl.2021.09.006.

Informed scenario-based RRT∗ for aircraft trajectory planning under ensemble forecasting of thunderstorms

E. Andrés; D. González-Arribas; M. Soler; M. Kamgarpour; M. Sanjurjo-Rivo 

Transportation Research Part C: Emerging Technologies. 2021. Vol. 129, p. 103232. DOI : 10.1016/j.trc.2021.103232.

On the Equivalence of Youla, System-Level, and Input-Output Parameterizations

Y. Zheng; L. Furieri; A. Papachristodoulou; N. Li; M. Kamgarpour 

IEEE Transactions on Automatic Control. 2021. Vol. 66, num. 1, p. 413 – 420. DOI : 10.1109/TAC.2020.2979785.

A market-based approach for enabling inter-area reserve exchange

O. Karaca; S. Delikaraoglou; M. Kamgarpour 

Operations Research Letters. 2021. Vol. 49, num. 4, p. 501 – 506. DOI : 10.1016/j.orl.2021.05.009.

2020

Safe non-smooth black-box optimization with application to policy search

I. Usmanova; A. Krause; M. Kamgarpour 

2020. Learning for Dynamics and Control, 2020-07-31. p. 980 – 989.

Learning the Globally Optimal Distributed LQ Regulator

L. Furieri; Y. Zheng; M. Kamgarpour 

2020. Learning for Dynamics and Control, 2020-07-31. p. 287 – 297.

First Order Methods For Globally Optimal Distributed Controllers Beyond Quadratic Invariance

L. Furieri; M. Kamgarpour 

2020. 2020 American Control Conference (ACC), Denver, CO, USA, 2020-07. p. 4588 – 4593. DOI : 10.23919/ACC45564.2020.9147358.

Mixed Strategies for Robust Optimization of Unknown Objectives

P. G. Sessa; I. Bogunovic; M. Kamgarpour; A. Krause 

2020. International Conference on Artificial Intelligence and Statistics, 2020-06-03. p. 2970 – 2980.

Distributed Design for Decentralized Control using Chordal Decomposition and ADMM

Y. Zheng; M. Kamgarpour; A. Sootla; A. Papachristodoulou 

IEEE Transactions on Control of Network Systems. 2020. Vol. 7, num. 2, p. 614 – 626. DOI : 10.1109/TCNS.2019.2935618.

System-level, Input-output and New Parameterizations of Stabilizing Controllers, and Their Numerical Computation

Y. Zheng; L. Furieri; M. Kamgarpour; N. Li 

2020

Minimizing Regret of Bandit Online Optimization in Unconstrained Action Spaces

T. Tatarenko; M. Kamgarpour 

2020

Safe Mission Planning under Dynamical Uncertainties

Y. Lu; M. Kamgarpour 

2020. 2020 IEEE International Conference on Robotics and Automation (ICRA), Paris, France, 2020-05. p. 2209 – 2215. DOI : 10.1109/ICRA40945.2020.9196515.

Core-Selecting Mechanisms in Electricity Markets

O. Karaca; M. Kamgarpour 

IEEE Transactions on Smart Grid. 2020. Vol. 11, num. 3, p. 2604 – 2614. DOI : 10.1109/TSG.2019.2958710.

Learning to Play Sequential Games versus Unknown Opponents

P. G. Sessa; I. Bogunovic; M. Kamgarpour; A. Krause 

2020.  p. 8971 – 8981.

Contextual Games: Multi-Agent Learning with Side Information

P. G. Sessa; I. Bogunovic; A. Krause; M. Kamgarpour 

2020.  p. 21912 – 21922.

Sparsity Invariance for Convex Design of Distributed Controllers

L. Furieri; Y. Zheng; A. Papachristodoulou; M. Kamgarpour 

IEEE Transactions on Control of Network Systems. 2020. Vol. 7, num. 4, p. 1836 – 1847. DOI : 10.1109/TCNS.2020.3002429.

A Multiagent Model of Efficient and Sustainable Financial Markets

B. Shea 

2020. Machine Learning for Economic Policy workshop, Vancouver, 2020.

No-Regret Learning from Partially Observed Data in Repeated Auctions

O. Karaca; P. G. Sessa; A. Leidi; M. Kamgarpour 

IFAC-PapersOnLine. 2020. Vol. 53, num. 2, p. 14 – 19. DOI : 10.1016/j.ifacol.2020.12.029.

Actuator Placement under Structural Controllability using Forward and Reverse Greedy Algorithms

B. Guo; O. Karaca; T. H. Summers; M. Kamgarpour 

IEEE Transactions on Automatic Control. 2020.  p. 1 – 1. DOI : 10.1109/TAC.2020.3044284.

2019

Enabling inter-area reserve exchange through stable benefit allocation mechanisms

O. Karaca; S. Delikaraoglou; G. Hug; M. Kamgarpour 

2019

Log Barriers for Safe Non-convex Black-box Optimization

I. Usmanova; A. Krause; M. Kamgarpour 

2019

Privacy of Real-Time Pricing in Smart Grid

M. Ghoddousi Boroujeni; D. Fay; C. Dimitrakakis; M. Kamgarpour 

2019. 2019 IEEE 58th Conference on Decision and Control (CDC), Nice, France, 2019-12. p. 5162 – 5167. DOI : 10.1109/CDC40024.2019.9029924.

Learning Nash Equilibria in Monotone Games

T. Tatarenko; M. Kamgarpour 

2019. 2019 IEEE 58th Conference on Decision and Control (CDC), Nice, France, 2019-12. p. 3104 – 3109. DOI : 10.1109/CDC40024.2019.9029659.

Actuator Placement for Optimizing Network Performance under Controllability Constraints

B. Guo; O. Karaca; T. Summers; M. Kamgarpour 

2019. 2019 IEEE 58th Conference on Decision and Control (CDC), Nice, France, 2019-12. p. 7140 – 7147. DOI : 10.1109/CDC40024.2019.9030204.

Unified Approach to Convex Robust Distributed Control Given Arbitrary Information Structures

L. Furieri; M. Kamgarpour 

IEEE Transactions on Automatic Control. 2019. Vol. 64, num. 12, p. 5199 – 5206. DOI : 10.1109/TAC.2019.2911655.

Designing Coalition-Proof Reverse Auctions Over Continuous Goods

O. Karaca; P. G. Sessa; N. Walton; M. Kamgarpour 

IEEE Transactions on Automatic Control. 2019. Vol. 64, num. 11, p. 4803 – 4810. DOI : 10.1109/TAC.2019.2908717.

An Input–Output Parametrization of Stabilizing Controllers: Amidst Youla and System Level Synthesis

L. Furieri; Y. Zheng; A. Papachristodoulou; M. Kamgarpour 

IEEE Control Systems Letters. 2019. Vol. 3, num. 4, p. 1014 – 1019. DOI : 10.1109/LCSYS.2019.2920205.

Exploiting structure of chance constrained programs via submodularity

D. Frick; P. G. Sessa; T. A. Wood; M. Kamgarpour 

Automatica. 2019. Vol. 105, p. 89 – 95. DOI : 10.1016/j.automatica.2019.03.027.

Strengthening the Group: Aggregated Frequency Reserve Bidding With ADMM

F. Rey; X. Zhang; S. Merkli; V. Agliati; M. Kamgarpour et al. 

IEEE Transactions on Smart Grid. 2019. Vol. 10, num. 4, p. 3860 – 3869. DOI : 10.1109/TSG.2018.2841508.

Robust aircraft trajectory planning under uncertain convective environments with optimal control and rapidly developing thunderstorms

D. González-Arribas; M. Soler; M. Sanjurjo-Rivo; M. Kamgarpour; J. Simarro 

Aerospace Science and Technology. 2019. Vol. 89, p. 445 – 459. DOI : 10.1016/j.ast.2019.03.051.

On Separable Quadratic Lyapunov Functions for Convex Design of Distributed Controllers

L. Furieri; Y. Zheng; A. Papachristodoulou; M. Kamgarpour 

2019. 2019 18th European Control Conference (ECC), Naples, Italy, 2019-06. p. 42 – 49. DOI : 10.23919/ECC.2019.8796100.

Performance guarantees for greedy maximization of non-submodular controllability metrics

T. Summers; M. Kamgarpour 

2019. 2019 18th European Control Conference (ECC), Naples, Italy, 2019-06. p. 2796 – 2801. DOI : 10.23919/ECC.2019.8795800.

Using Uncertainty Data in Chance-Constrained Trajectory Planning

V. Lefkopoulos; M. Kamgarpour 

2019. 2019 18th European Control Conference (ECC), Naples, Italy, 2019-06. p. 2264 – 2269. DOI : 10.23919/ECC.2019.8795823.

Bounding Inefficiency of Equilibria in Continuous Actions Games using Submodularity and Curvature

P. G. Sessa; M. Kamgarpour; A. Krause 

2019. The 22nd International Conference on Artificial Intelligence and Statistics, 2019-04-11. p. 2017 – 2027.

Safe Convex Learning under Uncertain Constraints

I. Usmanova; A. Krause; M. Kamgarpour 

2019. The 22nd International Conference on Artificial Intelligence and Statistics, 2019-04-11. p. 2106 – 2114.

Learning Generalized Nash Equilibria in a Class of Convex Games

T. Tatarenko; M. Kamgarpour 

IEEE Transactions on Automatic Control. 2019. Vol. 64, num. 4, p. 1426 – 1439. DOI : 10.1109/TAC.2018.2841319.

Nash and Wardrop Equilibria in Aggregative Games With Coupling Constraints

D. Paccagnan; B. Gentile; F. Parise; M. Kamgarpour; J. Lygeros 

IEEE Transactions on Automatic Control. 2019. Vol. 64, num. 4, p. 1373 – 1388. DOI : 10.1109/TAC.2018.2849946.

No-Regret Learning in Unknown Games with Correlated Payoffs

P. G. Sessa; I. Bogunovic; M. Kamgarpour; A. Krause 

2019. Advances in Neural Information Processing System, Vancouver, 2019.

2018

Exploiting Weak Supermodularity for Coalition-Proof Mechanisms

O. Karaca; M. Kamgarpour 

2018. 2018 IEEE Conference on Decision and Control (CDC), Miami Beach, FL, 2018-12. p. 1118 – 1123. DOI : 10.1109/CDC.2018.8619337.

Robust Distributed Control Beyond Quadratic Invariance

L. Furieri; M. Kamgarpour 

2018. 2018 IEEE Conference on Decision and Control (CDC), Miami Beach, FL, 2018-12. p. 3728 – 3733. DOI : 10.1109/CDC.2018.8619137.

Reducing HVDC Network Oscillations Considering Wind Intermittency Through Optimized Grid Expansion Decision

A. Elahidoost; L. Furieri; E. Tedeschi; M. Kamgarpour 

2018. 2018 IEEE Energy Conversion Congress and Exposition (ECCE), Portland, OR, USA, 2018-09. p. 2683 – 2690. DOI : 10.1109/ECCE.2018.8557546.

On maximizing safety in stochastic aircraft trajectory planning with uncertain thunderstorm development

D. Hentzen; M. Kamgarpour; M. Soler; D. González-Arribas 

Aerospace Science and Technology. 2018. Vol. 79, p. 543 – 553. DOI : 10.1016/j.ast.2018.06.006.

Game-theoretic models in energy systems and control DTU Summer School 2018 Modern Optimization in Energy Systems‬

M. Kamgarpour 

2018

Minimizing Regret in Unconstrained Online Convex Optimization

T. Tatarenko; M. Kamgarpour 

2018. 2018 17th European Control Conference (ECC), Limassol, 2018-06. p. 143 – 148. DOI : 10.23919/ECC.2018.8550310.

Optimizing HVDC Grid Expansion and Control for Enhancing DC Stability

A. Elahidoost; L. Furieri; E. Tedeschi; M. Kamgarpour 

2018. 2018 Power Systems Computation Conference (PSCC), Dublin, Ireland, 2018-06. p. 1 – 7. DOI : 10.23919/PSCC.2018.8442753.

Scalable analysis of linear networked systems via chordal decomposition

Y. Zheng; M. Kamgarpour; A. Sootla; A. Papachristodoulou 

2018. 2018 17th European Control Conference (ECC), Limassol, 2018-06. p. 2260 – 2265. DOI : 10.23919/ECC.2018.8550409.

From Uncertainty Data to Robust Policies for Temporal Logic Planning

P. G. Sessa; D. Frick; T. A. Wood; M. Kamgarpour 

2018. HSCC ’18: 21st International Conference on Hybrid Systems: Computation and Control, Porto Portugal, 2018-04-11. p. 157 – 166. DOI : 10.1145/3178126.3178136.

2017

Game theoretic analysis of electricity market auction mechanisms

O. Karaca; M. Kamgarpour 

2017. 2017 IEEE 56th Annual Conference on Decision and Control (CDC), Melbourne, Australia, 2017-12. p. 6211 – 6216. DOI : 10.1109/CDC.2017.8264596.

Robust control of constrained systems given an information structure

L. Furieri; M. Kamgarpour 

2017. 2017 IEEE 56th Annual Conference on Decision and Control (CDC), Melbourne, Australia, 2017-12. p. 3481 – 3486. DOI : 10.1109/CDC.2017.8264169.

The Linear Programming Approach to Reach-Avoid Problems for Markov Decision Processes

N. Kariotoglou; M. Kamgarpour; T. H. Summers; J. Lygeros 

Journal of Artificial Intelligence Research. 2017. Vol. 60, p. 263 – 285. DOI : 10.1613/jair.5500.

Exploring the Vickrey-Clarke-Groves Mechanism for Electricity Markets * *This work is partially funded under M. Kamgarpour’s European Union ERC Starting Grant CONENE.

P. G. Sessa; N. Walton; M. Kamgarpour 

IFAC-PapersOnLine. 2017. Vol. 50, num. 1, p. 189 – 194. DOI : 10.1016/j.ifacol.2017.08.032.

Sequential Linear Quadratic Optimal Control for Nonlinear Switched Systems

F. Farshidian; M. Kamgarpour; D. Pardo; J. Buchli 

IFAC-PapersOnLine. 2017. Vol. 50, num. 1, p. 1463 – 1469. DOI : 10.1016/j.ifacol.2017.08.291.

On infinite dimensional linear programming approach to stochastic control * *This research is partially supported by M. Kamgarpour’s European Union ERC Starting Grant, CONENE and by T. Summers’ the US National Science Foundation under grant CNS-1566127.

M. Kamgarpour; T. Summers 

IFAC-PapersOnLine. 2017. Vol. 50, num. 1, p. 6148 – 6153. DOI : 10.1016/j.ifacol.2017.08.979.

Robust Control Policies Given Formal Specifications in Uncertain Environments

D. Frick; T. A. Wood; G. Ulli; M. Kamgarpour 

IEEE Control Systems Letters. 2017. Vol. 1, num. 1, p. 20 – 25. DOI : 10.1109/LCSYS.2017.2700333.

Information Structure Design in Team Decision Problems

T. Summers; C. Li; M. Kamgarpour 

IFAC-PapersOnLine. 2017. Vol. 50, num. 1, p. 2530 – 2535. DOI : 10.1016/j.ifacol.2017.08.067.

Payoff-Based Approach to Learning Nash Equilibria in Convex Games * *This research is partially supported by M. Kamgarpour’s European Union ERC Starting Grant, CONENE.

T. Tatarenko; M. Kamgarpour 

IFAC-PapersOnLine. 2017. Vol. 50, num. 1, p. 1508 – 1513. DOI : 10.1016/j.ifacol.2017.08.300.

Optimal Aircraft Trajectory Planning in the Presence of Stochastic Convective Weather Cells

D. González-Arribas; D. Hentzen; M. Sanjurjo-Rivo; M. Soler; M. Kamgarpour 

2017. 17th AIAA Aviation Technology, Integration, and Operations Conference, Denver, Colorado, 2017-06-05. DOI : 10.2514/6.2017-3431.

Control synthesis for stochastic systems given automata specifications defined by stochastic sets

M. Kamgarpour; T. A. Wood; S. Summers; J. Lygeros 

Automatica. 2017. Vol. 76, p. 177 – 182. DOI : 10.1016/j.automatica.2016.10.013.