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ORCIDJalal Arabneydi
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2020 – today
- 2023
[i8]Md Saiful Islam, Srijita Das, Sai Krishna Gottipati, William Duguay, Clodéric Mars, Jalal Arabneydi, Antoine Fagette, Matthew Guzdial, Matthew E. Taylor:
Human-AI Collaboration in Real-World Complex Environment with Reinforcement Learning. CoRR abs/2312.15160 (2023)- 2021
- [c15]Jalal Arabneydi, Amir G. Aghdam:
Receding Horizon Control in Deep Structured Teams: A Provably Tractable Large-Scale Approach with Application to Swarm Robotics. CDC 2021: 6982-6989 - [c14]Jalal Arabneydi, Amir G. Aghdam:
Deep Structured Teams in Arbitrary-Size Linear Networks: Decentralized Estimation, Optimal Control and Separation Principle. CDC 2021: 6990-6996 - [i7]Jalal Arabneydi, Amir G. Aghdam:
Receding Horizon Control in Deep Structured Teams: A Provably Tractable Large-Scale Approach with Application to Swarm Robotics. CoRR abs/2110.10554 (2021) - [i6]Jalal Arabneydi, Amir G. Aghdam:
Deep Structured Teams in Arbitrary-Size Linear Networks: Decentralized Estimation, Optimal Control and Separation Principle. CoRR abs/2110.12217 (2021) - 2020
- [j3]Mohammad M. Baharloo, Jalal Arabneydi
, Amir G. Aghdam:
MinMax Mean-Field Team Approach for a Leader-Follower Network: A Saddle-Point Strategy. IEEE Control. Syst. Lett. 4(1): 121-126 (2020) - [j2]Jalal Arabneydi, Amir G. Aghdam:
Deep Teams: Decentralized Decision Making With Finite and Infinite Number of Agents. IEEE Trans. Autom. Control. 65(10): 4230-4245 (2020) - [j1]Jalal Arabneydi, Amir G. Aghdam:
Data Collection Versus Data Estimation: A Fundamental Trade-Off in Dynamic Networks. IEEE Trans. Netw. Sci. Eng. 7(3): 2000-2015 (2020) - [c13]Jalal Arabneydi, Masoud Roudneshin, Amir G. Aghdam:
Reinforcement Learning in Deep Structured Teams: Initial Results with Finite and Infinite Valued Features. CCTA 2020: 148-155 - [c12]Masoud Roudneshin, Jalal Arabneydi, Amir G. Aghdam:
Reinforcement Learning in Nonzero-sum Linear Quadratic Deep Structured Games: Global Convergence of Policy Optimization. CDC 2020: 512-517 - [c11]Vida Fathi, Jalal Arabneydi, Amir G. Aghdam:
Reinforcement Learning in Linear Quadratic Deep Structured Teams: Global Convergence of Policy Gradient Methods. CDC 2020: 4927-4932 - [i5]Jalal Arabneydi, Masoud Roudneshin, Amir G. Aghdam:
Reinforcement Learning in Deep Structured Teams: Initial Results with Finite and Infinite Valued Features. CoRR abs/2010.02868 (2020) - [i4]Masoud Roudneshin, Jalal Arabneydi, Amir G. Aghdam:
Reinforcement Learning in Nonzero-sum Linear Quadratic Deep Structured Games: Global Convergence of Policy Optimization. CoRR abs/2011.14391 (2020) - [i3]Vida Fathi, Jalal Arabneydi, Amir G. Aghdam:
Reinforcement Learning in Linear Quadratic Deep Structured Teams: Global Convergence of Policy Gradient Methods. CoRR abs/2011.14393 (2020) - [i2]Jalal Arabneydi, Amir G. Aghdam:
A Mean-Field Team Approach to Minimize the Spread of Infection in a Network. CoRR abs/2012.00232 (2020) - [i1]Jalal Arabneydi, Mohammad M. Baharloo, Amir G. Aghdam:
Optimal Distributed Control for Leader-Follower Networks: A Scalable Design. CoRR abs/2012.00239 (2020)
2010 – 2019
- 2019
- [c10]Jalal Arabneydi, Amir G. Aghdam:
A Mean-Field Team Approach to Minimize the Spread of Infection in a Network. ACC 2019: 2747-2752 - [d2]Jalal Arabneydi:
Data Collection versus Data Estimation: A Fundamental Trade-off in Dynamic Invariant Networks with Known and Unknown Models. IEEE DataPort, 2019
- [d1]Jalal Arabneydi:
Data Collection versus Data Estimation: A Fundamental Trade-off in Dynamic Invariant Networks with Known and Unknown Models. IEEE DataPort, 2019 - 2018
- [c9]Jalal Arabneydi, Amir G. Aghdam:
Optimal Dynamic Pricing for Binary Demands in Smart Grids: A Fair and Privacy-Preserving Strategy. ACC 2018: 5368-5373 - [c8]Jalal Arabneydi, Mohammad M. Baharloo, Amir G. Aghdam:
Optimal Distributed Control for Leader-Follower Networks: A Scalable Design. CCECE 2018: 1-4 - [c7]Mohammad M. Baharloo, Jalal Arabneydi, Amir G. Aghdam:
Near-Optimal Control Strategy in Leader-Follower Networks: A Case Study for Linear Quadratic Mean-Field Teams. CDC 2018: 3288-3293 - [c6]Jalal Arabneydi, Amir G. Aghdam:
Near-Optimal Design for Fault-Tolerant Systems with Homogeneous Components under Incomplete Information. MWSCAS 2018: 809-812 - 2017
- [c5]Jalal Arabneydi, Amir G. Aghdam:
A certainty equivalence result in team-optimal control of mean-field coupled Markov chains. CDC 2017: 3125-3130 - 2015
- [c4]Jalal Arabneydi, Aditya Mahajan:
Reinforcement learning in decentralized stochastic control systems with partial history sharing. ACC 2015: 5449-5456 - [c3]Jalal Arabneydi, Aditya Mahajan:
Team-optimal solution of finite number of mean-field coupled LQG subsystems. CDC 2015: 5308-5313 - 2014
- [c2]Jalal Arabneydi, Aditya Mahajan:
Team optimal control of coupled subsystems with mean-field sharing. CDC 2014: 1669-1674
2000 – 2009
- 2009
- [c1]Jalal Arabneydi, Behzad Moshiri, Fariba Bahrami:
Modeling Gait Using CPG (Central Pattern Generator) and Neural Network. COST 2101/2102 Conference 2009: 130-137
Coauthor Index
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