A Reinforcement Learning Based Method for Optimizing the Process of Decision Making in Fire Brigade Agents. - Abbas Abdolmaleki; Mostafa Movahedi; Sajjad Salehi; Nuno Lau; Luís Paulo Reis (EPIA, 2011)

A Distributed Cooperative Reinforcement Learning Method for Decision Making in Fire Brigade Teams. - Abbas Abdolmaleki; Mostafa Movahedi; Nuno Lau; Luís Paulo Reis (RoboCup, 2012)

A Model for Context Aware Mobile Payment. - Leila Abedi; Mohammad Ali Nematbakhsh; Abbas Abdolmaleki (J. Theor. Appl. Electron. Commer. Res., 2012)

Omnidirectional Walking and Active Balance for Soccer Humanoid Robot. - Nima Shafii; Abbas Abdolmaleki; Rui Ferreira 001; Nuno Lau; Luís Paulo Reis (EPIA, 2013)

Omnidirectional Walking with a Compliant Inverted Pendulum Model. - Abbas Abdolmaleki; Nima Shafii; Luís Paulo Reis; Nuno Lau; Jan Peters 001; Gerhard Neumann (IBERAMIA, 2014)

Regularized covariance estimation for weighted maximum likelihood policy search methods. - Abbas Abdolmaleki; Nuno Lau; Luís Paulo Reis; Gerhard Neumann (Humanoids, 2015)

Contextual Policy Search for Generalizing a Parameterized Biped Walking Controller. - Abbas Abdolmaleki; Nuno Lau; Luís Paulo Reis; Jan Peters 001; Gerhard Neumann (ICARSC, 2015)

Model-Based Relative Entropy Stochastic Search. - Abbas Abdolmaleki; Rudolf Lioutikov; Jan Peters 001; Nuno Lau; Luís Paulo Reis; Gerhard Neumann (NIPS, 2015)

Contextual Stochastic Search. - Abbas Abdolmaleki; Nuno Lau; Luís Paulo Reis; Gerhard Neumann (GECCO (Companion), 2016)

Contextual Relative Entropy Policy Search with Covariance Matrix Adaptation. - Abbas Abdolmaleki; David Simões 001; Nuno Lau; Luís Paulo Reis; Gerhard Neumann (ICARSC, 2016)

Model-Free Trajectory Optimization for Reinforcement Learning. - Riad Akrour; Gerhard Neumann; Hany Abdulsamad; Abbas Abdolmaleki (ICML, 2016)

Non-parametric contextual stochastic search. - Abbas Abdolmaleki; Nuno Lau; Luís Paulo Reis; Gerhard Neumann (IROS, 2016)

Learning a Humanoid Kick with Controlled Distance. - Abbas Abdolmaleki; David Simões 001; Nuno Lau; Luís Paulo Reis; Gerhard Neumann (RoboCup, 2016)

Contextual Policy Search for Linear and Nonlinear Generalization of a Humanoid Walking Controller. - Abbas Abdolmaleki; Nuno Lau; Luís Paulo Reis; Jan Peters 001; Gerhard Neumann (J. Intell. Robotic Syst., 2016)

Stochastic Search In Changing Situations. - Abbas Abdolmaleki; David Simões 001; Nuno Lau; Luís Paulo Reis; Bob Price; Gerhard Neumann (AAAI Workshops, 2017)

Deriving and improving CMA-ES with information geometric trust regions. - Abbas Abdolmaleki; Bob Price; Nuno Lau; Luís Paulo Reis; Gerhard Neumann (GECCO, 2017)

Contextual Covariance Matrix Adaptation Evolutionary Strategies. - Abbas Abdolmaleki; Bob Price; Nuno Lau; Luís Paulo Reis; Gerhard Neumann (IJCAI, 2017)

Maximum a Posteriori Policy Optimisation. - Abbas Abdolmaleki; Jost Tobias Springenberg; Yuval Tassa; Rémi Munos; Nicolas Heess; Martin A. Riedmiller (ICLR (Poster), 2018)

Guide Actor-Critic for Continuous Control. - Voot Tangkaratt; Abbas Abdolmaleki; Masashi Sugiyama (ICLR (Poster), 2018)

Eager and Memory-Based Non-Parametric Stochastic Search Methods for Learning Control. - Victor Barbaros; Herke van Hoof; Abbas Abdolmaleki; David Meger (ICRA, 2018)

DeepMind Control Suite. - Yuval Tassa; Yotam Doron; Alistair Muldal; Tom Erez; Yazhe Li; Diego de Las Casas; David Budden; Abbas Abdolmaleki; Josh Merel; Andrew Lefrancq; Timothy P. Lillicrap; Martin A. Riedmiller (CoRR, 2018)

Relative Entropy Regularized Policy Iteration. - Abbas Abdolmaleki; Jost Tobias Springenberg; Jonas Degrave; Steven Bohez; Yuval Tassa; Dan Belov; Nicolas Heess; Martin A. Riedmiller (CoRR, 2018)

Model-Free Trajectory-based Policy Optimization with Monotonic Improvement. - Riad Akrour; Abbas Abdolmaleki; Hany Abdulsamad; Jan Peters 001; Gerhard Neumann (J. Mach. Learn. Res., 2018)

Information theoretic stochastic search - Abbas Abdolmaleki (2018)

Imagined Value Gradients: Model-Based Policy Optimization with Tranferable Latent Dynamics Models. - Arunkumar Byravan; Jost Tobias Springenberg; Abbas Abdolmaleki; Roland Hafner; Michael Neunert; Thomas Lampe; Noah Y. Siegel; Nicolas Heess; Martin A. Riedmiller (CoRL, 2019)

Continuous-Discrete Reinforcement Learning for Hybrid Control in Robotics. - Michael Neunert; Abbas Abdolmaleki; Markus Wulfmeier; Thomas Lampe; Jost Tobias Springenberg; Roland Hafner; Francesco Romano; Jonas Buchli; Nicolas Heess; Martin A. Riedmiller (CoRL, 2019)

Simultaneously Learning Vision and Feature-Based Control Policies for Real-World Ball-In-A-Cup. - Devin Schwab; Jost Tobias Springenberg; Murilo Fernandes Martins; Michael Neunert; Thomas Lampe; Abbas Abdolmaleki; Tim Hertweck; Roland Hafner; Francesco Nori; Martin A. Riedmiller (Robotics: Science and Systems, 2019)

Value constrained model-free continuous control. - Steven Bohez; Abbas Abdolmaleki; Michael Neunert; Jonas Buchli; Nicolas Heess; Raia Hadsell (CoRR, 2019)

Robust Reinforcement Learning for Continuous Control with Model Misspecification. - Daniel J. Mankowitz; Nir Levine; Rae Jeong; Abbas Abdolmaleki; Jost Tobias Springenberg; Timothy A. Mann; Todd Hester; Martin A. Riedmiller (CoRR, 2019)

Regularized Hierarchical Policies for Compositional Transfer in Robotics. - Markus Wulfmeier; Abbas Abdolmaleki; Roland Hafner; Jost Tobias Springenberg; Michael Neunert; Tim Hertweck; Thomas Lampe; Noah Y. Siegel; Nicolas Heess; Martin A. Riedmiller (CoRR, 2019)

Augmenting learning using symmetry in a biologically-inspired domain. - Shruti Mishra; Abbas Abdolmaleki; Arthur Guez; Piotr Trochim; Doina Precup (CoRR, 2019)

Imagined Value Gradients: Model-Based Policy Optimization with Transferable Latent Dynamics Models. - Arunkumar Byravan; Jost Tobias Springenberg; Abbas Abdolmaleki; Roland Hafner; Michael Neunert; Thomas Lampe; Noah Y. Siegel; Nicolas Heess; Martin A. Riedmiller (CoRR, 2019)

Modelling Generalized Forces with Reinforcement Learning for Sim-to-Real Transfer. - Rae Jeong; Jackie Kay; Francesco Romano; Thomas Lampe; Thomas Rothörl; Abbas Abdolmaleki; Tom Erez; Yuval Tassa; Francesco Nori (CoRR, 2019)

Quinoa: a Q-function You Infer Normalized Over Actions. - Jonas Degrave; Abbas Abdolmaleki; Jost Tobias Springenberg; Nicolas Heess; Martin A. Riedmiller (CoRR, 2019)

Contextual Direct Policy Search - With Regularized Covariance Matrix Estimation. - Abbas Abdolmaleki; David Simões 001; Nuno Lau; Luís Paulo Reis; Gerhard Neumann (J. Intell. Robotic Syst., 2019)

Robust Reinforcement Learning for Continuous Control with Model Misspecification. - Daniel J. Mankowitz; Nir Levine; Rae Jeong; Abbas Abdolmaleki; Jost Tobias Springenberg; Yuanyuan Shi; Jackie Kay; Todd Hester; Timothy A. Mann; Martin A. Riedmiller (ICLR, 2020)

Keep Doing What Worked: Behavior Modelling Priors for Offline Reinforcement Learning. - Noah Y. Siegel; Jost Tobias Springenberg; Felix Berkenkamp; Abbas Abdolmaleki; Michael Neunert; Thomas Lampe; Roland Hafner; Nicolas Heess; Martin A. Riedmiller (ICLR, 2020)

V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control. - H. Francis Song; Abbas Abdolmaleki; Jost Tobias Springenberg; Aidan Clark; Hubert Soyer; Jack W. Rae; Seb Noury; Arun Ahuja; Siqi Liu 002; Dhruva Tirumala; Nicolas Heess; Dan Belov; et al. (ICLR, 2020)

A distributional view on multi-objective policy optimization. - Abbas Abdolmaleki; Sandy H. Huang; Leonard Hasenclever; Michael Neunert; H. Francis Song; Martina Zambelli; Murilo F. Martins; Nicolas Heess; Raia Hadsell; Martin A. Riedmiller (ICML, 2020)

Compositional Transfer in Hierarchical Reinforcement Learning. - Markus Wulfmeier; Abbas Abdolmaleki; Roland Hafner; Jost Tobias Springenberg; Michael Neunert; Noah Y. Siegel; Tim Hertweck; Thomas Lampe; Nicolas Heess; Martin A. Riedmiller (Robotics: Science and Systems, 2020)

Keep Doing What Worked: Behavioral Modelling Priors for Offline Reinforcement Learning. - Noah Y. Siegel; Jost Tobias Springenberg; Felix Berkenkamp; Abbas Abdolmaleki; Michael Neunert; Thomas Lampe; Roland Hafner; Nicolas Heess; Martin A. Riedmiller (CoRR, 2020)

Acme: A Research Framework for Distributed Reinforcement Learning. - Matt Hoffman 001; Bobak Shahriari; John Aslanides; Gabriel Barth-Maron; Feryal M. P. Behbahani; Tamara Norman; Abbas Abdolmaleki; Albin Cassirer; Fan Yang; Kate Baumli; Sarah Henderson; Alexander Novikov 001; et al. (CoRR, 2020)

Local Search for Policy Iteration in Continuous Control. - Jost Tobias Springenberg; Nicolas Heess; Daniel J. Mankowitz; Josh Merel; Arunkumar Byravan; Abbas Abdolmaleki; Jackie Kay; Jonas Degrave; Julian Schrittwieser; Yuval Tassa; Jonas Buchli; Dan Belov; et al. (CoRR, 2020)

"What, not how": Solving an under-actuated insertion task from scratch. - Giulia Vezzani; Michael Neunert; Markus Wulfmeier; Rae Jeong; Thomas Lampe; Noah Y. Siegel; Roland Hafner; Abbas Abdolmaleki; Martin A. Riedmiller; Francesco Nori (CoRR, 2020)

A Constrained Multi-Objective Reinforcement Learning Framework. - Sandy H. Huang; Abbas Abdolmaleki; Giulia Vezzani; Philemon Brakel; Daniel J. Mankowitz; Michael Neunert; Steven Bohez; Yuval Tassa; Nicolas Heess; Martin A. Riedmiller; Raia Hadsell (CoRL, 2021)

Beyond Pick-and-Place: Tackling Robotic Stacking of Diverse Shapes. - Alex X. Lee; Coline Manon Devin; Yuxiang Zhou; Thomas Lampe; Konstantinos Bousmalis; Jost Tobias Springenberg; Arunkumar Byravan; Abbas Abdolmaleki; Nimrod Gileadi; David Khosid; Claudio Fantacci; José Enrique Chen; et al. (CoRL, 2021)

Data-efficient Hindsight Off-policy Option Learning. - Markus Wulfmeier; Dushyant Rao; Roland Hafner; Thomas Lampe; Abbas Abdolmaleki; Tim Hertweck; Michael Neunert; Dhruva Tirumala; Noah Y. Siegel; Nicolas Heess; Martin A. Riedmiller (ICML, 2021)

Rethinking Exploration for Sample-Efficient Policy Learning. - William F. Whitney; Michael Bloesch; Jost Tobias Springenberg; Abbas Abdolmaleki; Martin A. Riedmiller (CoRR, 2021)

On Multi-objective Policy Optimization as a Tool for Reinforcement Learning. - Abbas Abdolmaleki; Sandy H. Huang; Giulia Vezzani; Bobak Shahriari; Jost Tobias Springenberg; Shruti Mishra; Dhruva TB; Arunkumar Byravan; Konstantinos Bousmalis; András György 001; Csaba Szepesvári; Raia Hadsell; et al. (CoRR, 2021)

Forgetting and Imbalance in Robot Lifelong Learning with Off-policy Data. - Wenxuan Zhou; Steven Bohez; Jan Humplik; Nicolas Heess; Abbas Abdolmaleki; Dushyant Rao; Markus Wulfmeier; Tuomas Haarnoja (CoLLAs, 2022)

Evaluating Model-Based Planning and Planner Amortization for Continuous Control. - Arunkumar Byravan; Leonard Hasenclever; Piotr Trochim; Mehdi Mirza; Alessandro Davide Ialongo; Yuval Tassa; Jost Tobias Springenberg; Abbas Abdolmaleki; Nicolas Heess; Josh Merel; Martin A. Riedmiller (ICLR, 2022)

How to Spend Your Robot Time: Bridging Kickstarting and Offline Reinforcement Learning for Vision-based Robotic Manipulation. - Alex X. Lee; Coline Devin; Jost Tobias Springenberg; Yuxiang Zhou; Thomas Lampe; Abbas Abdolmaleki; Konstantinos Bousmalis (IROS, 2022)

Offline Distillation for Robot Lifelong Learning with Imbalanced Experience. - Wenxuan Zhou; Steven Bohez; Jan Humplik; Abbas Abdolmaleki; Dushyant Rao; Markus Wulfmeier; Tuomas Haarnoja; Nicolas Heess (CoRR, 2022)

Revisiting Gaussian mixture critics in off-policy reinforcement learning: a sample-based approach. - Bobak Shahriari; Abbas Abdolmaleki; Arunkumar Byravan; Abe Friesen; Siqi Liu 002; Jost Tobias Springenberg; Nicolas Heess; Matt Hoffman 001; Martin A. Riedmiller (CoRR, 2022)

Magnetic control of tokamak plasmas through deep reinforcement learning. - Jonas Degrave; Federico Felici; Jonas Buchli; Michael Neunert; Brendan D. Tracey; Francesco Carpanese; Timo Ewalds; Roland Hafner; Abbas Abdolmaleki; Diego de Las Casas; Craig Donner; Leslie Fritz; et al. (Nat., 2022)

From motor control to team play in simulated humanoid football. - Siqi Liu 002; Guy Lever; Zhe Wang 055; Josh Merel; S. M. Ali Eslami; Daniel Hennes; Wojciech M. Czarnecki; Yuval Tassa; Shayegan Omidshafiei; Abbas Abdolmaleki; Noah Y. Siegel; Leonard Hasenclever; et al. (Sci. Robotics, 2022)

Figure Data for the paper "From Motor Control to Team Play in Simulated Humanoid Football". - Siqi Liu 002; Guy Lever; Zhe Wang 055; Josh Merel; S. M. Ali Eslami; Daniel Hennes; Wojciech Czarnecki 001; Yuval Tassa; Shayegan Omidshafiei; Abbas Abdolmaleki; Noah Y. Siegel; Leonard Hasenclever; et al. (Zenodo, 2022)

Leveraging Jumpy Models for Planning and Fast Learning in Robotic Domains. - Jingwei Zhang 001; Jost Tobias Springenberg; Arunkumar Byravan; Leonard Hasenclever; Abbas Abdolmaleki; Dushyant Rao; Nicolas Heess; Martin A. Riedmiller (CoRR, 2023)

RoboCat: A Self-Improving Foundation Agent for Robotic Manipulation. - Konstantinos Bousmalis; Giulia Vezzani; Dushyant Rao; Coline Devin; Alex X. Lee; Maria Bauzá 001; Todor Davchev; Yuxiang Zhou; Agrim Gupta; Akhil Raju; Antoine Laurens; Claudio Fantacci; et al. (CoRR, 2023)

Policy composition in reinforcement learning via multi-objective policy optimization. - Shruti Mishra; Ankit Anand; Jordan Hoffmann; Nicolas Heess; Martin A. Riedmiller; Abbas Abdolmaleki; Doina Precup (CoRR, 2023)

SkillS: Adaptive Skill Sequencing for Efficient Temporally-Extended Exploration. - Giulia Vezzani; Dhruva Tirumala; Markus Wulfmeier; Dushyant Rao; Abbas Abdolmaleki; Ben Moran; Tuomas Haarnoja; Jan Humplik; Roland Hafner; Michael Neunert; Claudio Fantacci; Tim Hertweck; et al. (Trans. Mach. Learn. Res., 2023)

Offline Actor-Critic Reinforcement Learning Scales to Large Models. - Jost Tobias Springenberg; Abbas Abdolmaleki; Jingwei Zhang 001; Oliver Groth; Michael Bloesch; Thomas Lampe; Philemon Brakel; Sarah Bechtle; Steven Kapturowski; Roland Hafner; Nicolas Heess; Martin A. Riedmiller (ICML, 2024)

Mastering Stacking of Diverse Shapes with Large-Scale Iterative Reinforcement Learning on Real Robots. - Thomas Lampe; Abbas Abdolmaleki; Sarah Bechtle; Sandy H. Huang; Jost Tobias Springenberg; Michael Bloesch; Oliver Groth; Roland Hafner; Tim Hertweck; Michael Neunert; Markus Wulfmeier; Jingwei Zhang 001; et al. (ICRA, 2024)

Real-world fluid directed rigid body control via deep reinforcement learning. - Mohak Bhardwaj; Thomas Lampe; Michael Neunert; Francesco Romano; Abbas Abdolmaleki; Arunkumar Byravan; Markus Wulfmeier; Martin A. Riedmiller; Jonas Buchli (L4DC, 2024)

Game On: Towards Language Models as RL Experimenters. - Jingwei Zhang 001; Thomas Lampe; Abbas Abdolmaleki; Jost Tobias Springenberg; Martin A. Riedmiller (CoRR, 2024)

Preference Optimization as Probabilistic Inference. - Abbas Abdolmaleki; Bilal Piot; Bobak Shahriari; Jost Tobias Springenberg; Tim Hertweck; Rishabh Joshi; Junhyuk Oh; Michael Bloesch; Thomas Lampe; Nicolas Heess; Jonas Buchli; Martin A. Riedmiller (CoRR, 2024)

RoboCat: A Self-Improving Generalist Agent for Robotic Manipulation. - Konstantinos Bousmalis; Giulia Vezzani; Dushyant Rao; Coline Manon Devin; Alex X. Lee; Maria Bauzá Villalonga; Todor Davchev; Yuxiang Zhou; Agrim Gupta; Akhil Raju; Antoine Laurens; Claudio Fantacci; et al. (Trans. Mach. Learn. Res., 2024)

Learning from negative feedback, or positive feedback or both. - Abbas Abdolmaleki; Bilal Piot; Bobak Shahriari; Jost Tobias Springenberg; Tim Hertweck; Michael Bloesch; Rishabh Joshi; Thomas Lampe; Junhyuk Oh; Nicolas Heess; Jonas Buchli; Martin A. Riedmiller (ICLR, 2025)

Value from Observations: Towards Large-Scale Imitation Learning via Self-Improvement. - Michael Bloesch; Markus Wulfmeier; Philemon Brakel; Todor Davchev; Martina Zambelli; Jost Tobias Springenberg; Abbas Abdolmaleki; William F. Whitney; Nicolas Heess; Roland Hafner; Martin A. Riedmiller (CoRR, 2025)