Majid Mazouchi

Orcid: 0000-0003-2069-8760

According to our database1, Majid Mazouchi authored at least 20 papers between 2018 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Online presence:

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Bibliography

2023
Fixed-Time System Identification Using Concurrent Learning.
IEEE Trans. Neural Networks Learn. Syst., August, 2023

A Risk-Averse Preview-Based Q-Learning Algorithm: Application to Highway Driving of Autonomous Vehicles.
IEEE Trans. Control. Syst. Technol., July, 2023

Secure Event-Triggered Distributed Kalman Filters for State Estimation Over Wireless Sensor Networks.
IEEE Trans. Syst. Man Cybern. Syst., 2023

Finite-time Koopman Identifier: A Unified Batch-online Learning Framework for Joint Learning of Koopman Structure and Parameters.
J. Mach. Learn. Res., 2023

2022
Data-Driven Dynamic Multiobjective Optimal Control: An Aspiration-Satisfying Reinforcement Learning Approach.
IEEE Trans. Neural Networks Learn. Syst., 2022

Fully Heterogeneous Containment Control of a Network of Leader-Follower Systems.
IEEE Trans. Autom. Control., 2022

Conflict-Aware Safe Reinforcement Learning: A Meta-Cognitive Learning Framework.
IEEE CAA J. Autom. Sinica, 2022

Data-driven Robust LQR with Multiplicative Noise via System Level Synthesis.
CoRR, 2022

Performance Analysis of Event-Triggered Consensus Control for Multi-agent Systems under Cyber-Physical Attacks.
CoRR, 2022

Performance Analysis of Event-Triggered Consensus Control for Multi-agent Systems under Cyber-Physical Attacks.
Proceedings of the American Control Conference, 2022

2021
Memory-Augmented System Identification With Finite-Time Convergence.
IEEE Control. Syst. Lett., 2021

A Convex Programming Approach to Data-Driven Risk-Averse Reinforcement Learning.
CoRR, 2021

Assured Learning-enabled Autonomy: A Metacognitive Reinforcement Learning Framework.
CoRR, 2021

A One-shot Convex Optimization Approach to Risk-Averse Q-Learning.
Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

Learning Dynamics System Models with Prescribed-Performance Guarantees using Experience-Replay.
Proceedings of the 2021 American Control Conference, 2021

2020
Data-driven Dynamic Multi-objective Optimal Control: An Aspiration-satisfying Reinforcement Learning Approach.
CoRR, 2020

Fully-HeterogeneousContainment Control of a Network of Leader-Follower Systems.
CoRR, 2020

Data-Driven Solutions to Mixed $H_{2}/H_{\infty}$ Control: A Hamilton-Inequality-Driven Reinforcement Learning Approach.
Proceedings of the 2020 IEEE Conference on Control Technology and Applications, 2020

2018
A novel distributed optimal adaptive control algorithm for nonlinear multi-agent differential graphical games.
IEEE CAA J. Autom. Sinica, 2018

Observer-based Adaptive Optimal Output Containment Control problem of Linear Heterogeneous Multi-agent Systems with Relative Output Measurements.
CoRR, 2018


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