Behavior hierarchy learning in a behavior-based system using reinforcement learning. - Amir Massoud Farahmand; Majid Nili Ahmadabadi; Babak Nadjar Araabi (IROS, 2004)

Locally Optimal Takagi-Sugeno Fuzzy Controllers. - Amir Massoud Farahmand; Mohammad Javad Yazdanpanah (CDC/ECC, 2005)

Hybrid Behavior Co-evolution and Structure Learning in Behavior-based Systems. - Amir Massoud Farahmand; Majid Nili Ahmadabadi; Caro Lucas; Babak Nadjar Araabi (IEEE Congress on Evolutionary Computation, 2006)

Learning to Coordinate Behaviors in Soft Behavior-Based Systems Using Reinforcement Learning. - Mohammad G. Azar; Majid Nili Ahmadabadi; Amir Massoud Farahmand; Babak Nadjar Araabi (IJCNN, 2006)

Channel Assignment using Chaotic Simulated Annealing Enhanced Hopfield Neural Network. - Amir Massoud Farahmand; Mohammad Javad Yazdanpanah (IJCNN, 2006)

Manifold-adaptive dimension estimation. - Amir Massoud Farahmand; Csaba Szepesvári; Jean-Yves Audibert (ICML, 2007)

Global visual-motor estimation for uncalibrated visual servoing. - Amir Massoud Farahmand; Azad Shademan; Martin Jägersand (IROS, 2007)

Regularized Fitted Q-Iteration: Application to Planning. - Amir Massoud Farahmand; Mohammad Ghavamzadeh; Csaba Szepesvári; Shie Mannor (EWRL, 2008)

Regularized Policy Iteration. - Amir Massoud Farahmand; Mohammad Ghavamzadeh; Csaba Szepesvári; Shie Mannor (NIPS, 2008)

Regularized Fitted Q-Iteration for planning in continuous-space Markovian decision problems. - Amir Massoud Farahmand; Mohammad Ghavamzadeh; Csaba Szepesvári; Shie Mannor (ACC, 2009)

Towards Learning Robotic Reaching and Pointing: An Uncalibrated Visual Servoing Approach. - Azad Shademan; Amir Massoud Farahmand; Martin Jägersand (CRV, 2009)

Model-based and model-free reinforcement learning for visual servoing. - Amir Massoud Farahmand; Azad Shademan; Martin Jägersand; Csaba Szepesvári (ICRA, 2009)

Robust Jacobian estimation for uncalibrated visual servoing. - Azad Shademan; Amir Massoud Farahmand; Martin Jägersand (ICRA, 2010)

Error Propagation for Approximate Policy and Value Iteration. - Amir Massoud Farahmand; Rémi Munos; Csaba Szepesvári (NIPS, 2010)

Interaction of Culture-Based Learning and Cooperative Co-Evolution and its Application to Automatic Behavior-Based System Design. - Amir Massoud Farahmand; Majid Nili Ahmadabadi; Caro Lucas; Babak Nadjar Araabi (IEEE Trans. Evol. Comput., 2010)

Action-Gap Phenomenon in Reinforcement Learning. - Amir Massoud Farahmand (NIPS, 2011)

Model selection in reinforcement learning. - Amir Massoud Farahmand; Csaba Szepesvári (Mach. Learn., 2011)

Value Pursuit Iteration. - Amir Massoud Farahmand; Doina Precup (NIPS, 2012)

Bellman Error Based Feature Generation using Random Projections on Sparse Spaces. - Mahdi Milani Fard; Yuri Grinberg; Amir-massoud Farahmand; Joelle Pineau; Doina Precup (NIPS, 2013)

Learning from Limited Demonstrations. - Beomjoon Kim; Amir-massoud Farahmand; Joelle Pineau; Doina Precup (NIPS, 2013)

Sample-based approximate regularization. - Philip Bachman; Amir-massoud Farahmand; Doina Precup (ICML, 2014)

Classification-based Approximate Policy Iteration: Experiments and Extended Discussions. - Amir-massoud Farahmand; Doina Precup; André da Motta Salles Barreto; Mohammad Ghavamzadeh (CoRR, 2014)

Approximate MaxEnt Inverse Optimal Control and Its Application for Mental Simulation of Human Interactions. - De-An Huang; Amir-massoud Farahmand; Kris M. Kitani; James Andrew Bagnell (AAAI, 2015)

Reports of the AAAI 2014 Conference Workshops. - Stefano V. Albrecht; André da Motta Salles Barreto; Darius Braziunas; David L. Buckeridge; Heriberto Cuayáhuitl; Nina Dethlefs; Markus Endres; Amir-massoud Farahmand; Mark Fox; Lutz Frommberger; Sam Ganzfried; Yolanda Gil; et al. (AI Mag., 2015)

Classification-Based Approximate Policy Iteration. - Amir-massoud Farahmand; Doina Precup; André da Motta Salles Barreto; Mohammad Ghavamzadeh (IEEE Trans. Autom. Control., 2015)

Truncated Approximate Dynamic Programming with Task-Dependent Terminal Value. - Amir-massoud Farahmand; Daniel Nikolaev Nikovski; Yuji Igarashi; Hiroki Konaka (AAAI, 2016)

Learning-based modular indirect adaptive control for a class of nonlinear systems. - Mouhacine Benosman; Amir-massoud Farahmand; Meng Xia (ACC, 2016)

Learning to control partial differential equations: Regularized Fitted Q-Iteration approach. - Amir-massoud Farahmand; Saleh Nabi; Piyush Grover; Daniel Nikovski (CDC, 2016)

Regularized Policy Iteration with Nonparametric Function Spaces. - Amir-massoud Farahmand; Mohammad Ghavamzadeh; Csaba Szepesvári; Shie Mannor (J. Mach. Learn. Res., 2016)

Value-Aware Loss Function for Model-based Reinforcement Learning. - Amir Massoud Farahmand; André Barreto 001; Daniel Nikovski (AISTATS, 2017)

Deep reinforcement learning for partial differential equation control. - Amir-massoud Farahmand; Saleh Nabi; Daniel Nikolaev Nikovski (ACC, 2017)

Random Projection Filter Bank for Time Series Data. - Amir-massoud Farahmand; Sepideh Pourazarm; Daniel Nikovski (NIPS, 2017)

Learning to regulate rolling ball motion. - Devesh K. Jha; Daniel Nikovski; William Yerazunis; Amir-massoud Farahmand (SSCI, 2017)

Attentional Network for Visual Object Detection. - Kota Hara; Ming-Yu Liu 001; Oncel Tuzel; Amir-massoud Farahmand (CoRR, 2017)

Reinforcement Learning with Function-Valued Action Spaces for Partial Differential Equation Control. - Yangchen Pan; Amir-massoud Farahmand; Martha White; Saleh Nabi; Piyush Grover; Daniel Nikovski (ICML, 2018)

Iterative Value-Aware Model Learning. - Amir-massoud Farahmand (NeurIPS, 2018)

Improving Skin Condition Classification with a Question Answering Model. - Mohamed Akrout; Amir-massoud Farahmand; Tory Jarmain (CoRR, 2018)

Dimensionality Reduction for Representing the Knowledge of Probabilistic Models. - Marc T. Law; Jake Snell; Amir-massoud Farahmand; Raquel Urtasun; Richard S. Zemel (ICLR (Poster), 2019)

Hill Climbing on Value Estimates for Search-control in Dyna. - Yangchen Pan; Hengshuai Yao; Amir-massoud Farahmand; Martha White (IJCAI, 2019)

Improving Skin Condition Classification with a Visual Symptom Checker Trained Using Reinforcement Learning. - Mohamed Akrout; Amir-massoud Farahmand; Tory Jarmain; Latif Abid (MICCAI (4), 2019)

Value Function in Frequency Domain and the Characteristic Value Iteration Algorithm. - Amir-massoud Farahmand (NeurIPS, 2019)

Frequency-based Search-control in Dyna. - Yangchen Pan; Jincheng Mei; Amir-massoud Farahmand (ICLR, 2020)

An implicit function learning approach for parametric modal regression. - Yangchen Pan; Ehsan Imani; Amir-massoud Farahmand; Martha White (NeurIPS, 2020)

Policy-Aware Model Learning for Policy Gradient Methods. - Romina Abachi; Mohammad Ghavamzadeh; Amir-massoud Farahmand (CoRR, 2020)

Adversarial Robustness through Regularization: A Second-Order Approach. - Avery Ma; Fartash Faghri; Amir-massoud Farahmand (CoRR, 2020)

Beyond Prioritized Replay: Sampling States in Model-Based RL via Simulated Priorities. - Jincheng Mei; Yangchen Pan; Martha White; Amir-massoud Farahmand; Hengshuai Yao (CoRR, 2020)

The act of remembering: a study in partially observable reinforcement learning. - Rodrigo Toro Icarte; Richard Anthony Valenzano; Toryn Q. Klassen; Phillip J. K. Christoffersen; Amir-massoud Farahmand; Sheila A. McIlraith (CoRR, 2020)

PID Accelerated Value Iteration Algorithm. - Amir Massoud Farahmand; Mohammad Ghavamzadeh (ICML, 2021)

Deep Reinforcement Learning for Online Control of Stochastic Partial Differential Equations. - Erfan Pirmorad; Faraz Khoshbakhtian; Farnam Mansouri; Amir-massoud Farahmand (CoRR, 2021)

Learning Object-Oriented Dynamics for Planning from Text. - Guiliang Liu; Ashutosh Adhikari; Amir-massoud Farahmand; Pascal Poupart (ICLR, 2022)

Value Gradient weighted Model-Based Reinforcement Learning. - Claas Voelcker; Victor Liao; Animesh Garg; Amir-massoud Farahmand (ICLR, 2022)

Operator Splitting Value Iteration. - Amin Rakhsha; Andrew Wang; Mohammad Ghavamzadeh; Amir-massoud Farahmand (NeurIPS, 2022)

Understanding and mitigating the limitations of prioritized experience replay. - Yangchen Pan; Jincheng Mei; Amir-massoud Farahmand; Martha White; Hengshuai Yao; Mohsen Rohani; Jun Luo 009 (UAI, 2022)

Distributional Model Equivalence for Risk-Sensitive Reinforcement Learning. - Tyler Kastner; Murat A. Erdogdu; Amir-massoud Farahmand (NeurIPS, 2023)

λ-AC: Learning latent decision-aware models for reinforcement learning in continuous state-spaces. - Claas Voelcker; Arash Ahmadian; Romina Abachi; Igor Gilitschenski; Amir-massoud Farahmand (CoRR, 2023)

Understanding the robustness difference between stochastic gradient descent and adaptive gradient methods. - Avery Ma; Yangchen Pan; Amir-massoud Farahmand (Trans. Mach. Learn. Res., 2023)

Improving Adversarial Transferability via Model Alignment. - Avery Ma; Amir-massoud Farahmand; Yangchen Pan; Philip Torr 001; Jindong Gu (ECCV (62), 2024)

Maximum Entropy Model Correction in Reinforcement Learning. - Amin Rakhsha; Mete Kemertas; Mohammad Ghavamzadeh; Amir-massoud Farahmand (ICLR, 2024)

PID Accelerated Temporal Difference Algorithms. - Mark Bedaywi; Amin Rakhsha; Amir-massoud Farahmand (RLJ, 2024)

Dissecting Deep RL with High Update Ratios: Combatting Value Divergence. - Marcel Hussing; Claas Voelcker; Igor Gilitschenski; Amir-massoud Farahmand; Eric Eaton (RLJ, 2024)

When does Self-Prediction help? Understanding Auxiliary Tasks in Reinforcement Learning. - Claas Voelcker; Tyler Kastner; Igor Gilitschenski; Amir-massoud Farahmand (RLJ, 2024)

Dissecting Deep RL with High Update Ratios: Combatting Value Overestimation and Divergence. - Marcel Hussing; Claas Voelcker; Igor Gilitschenski; Amir-massoud Farahmand; Eric Eaton (CoRR, 2024)

A Truncated Newton Method for Optimal Transport. - Mete Kemertas; Amir-massoud Farahmand; Allan Douglas Jepson (ICLR, 2025)

MAD-TD: Model-Augmented Data stabilizes High Update Ratio RL. - Claas Voelcker; Marcel Hussing; Eric Eaton; Amir-massoud Farahmand; Igor Gilitschenski (ICLR, 2025)

Efficient and Accurate Optimal Transport with Mirror Descent and Conjugate Gradients. - Mete Kemertas; Allan Douglas Jepson; Amir-massoud Farahmand (Trans. Mach. Learn. Res., 2025)

Deflated Dynamics Value Iteration. - Jongmin Lee; Amin Rakhsha; Ernest K. Ryu; Amir-massoud Farahmand (Trans. Mach. Learn. Res., 2025)

PANDAS: Improving Many-shot Jailbreaking via Positive Affirmation, Negative Demonstration, and Adaptive Sampling. - Avery Ma; Yangchen Pan; Amir-massoud Farahmand (CoRR, 2025)

Calibrated Value-Aware Model Learning with Stochastic Environment Models. - Claas Voelcker; Anastasiia Pedan; Arash Ahmadian; Romina Abachi; Igor Gilitschenski; Amir-massoud Farahmand (CoRR, 2025)

Relative Entropy Pathwise Policy Optimization. - Claas Voelcker; Axel Brunnbauer; Marcel Hussing; Michal Nauman; Pieter Abbeel; Eric Eaton; Radu Grosu; Amir-massoud Farahmand; Igor Gilitschenski (CoRR, 2025)