Haitham Bou-Ammar

141 papers A* 28A 8B 3C 3Misc 2Journal 88Unranked 9

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Brain-like Synergistic Core in LLMs Drives Behaviour and Learning. CoRR Pedro Urbina-Rodriguez, Zafeirios Fountas, Fernando E. Rosas, Jun Wang, Andrea I. Luppi, Haitham Bou-Ammar, Murray Shanahan, Pedro A. M. Mediano
2026	J	`jnl`	A Pragmatist Robot: Learning to Plan Tasks by Experiencing the Real World. IEEE Robotics Autom. Lett. Kaixian Qu, Guowei Lan, René Zurbrügg, Changan Chen, Christopher E. Mower, Haitham Bou-Ammar, Marco Hutter
2026	J	`jnl`	Decoding as Optimisation on the Probability Simplex: From Top-K to Top-P (Nucleus) to Best-of-K Samplers. CoRR Xiaotong Ji, Rasul Tutunov, Matthieu Zimmer, Haitham Bou-Ammar
2026	J	`jnl`	Multi-Task GRPO: Reliable LLM Reasoning Across Tasks. CoRR Shyam Sundhar Ramesh, Xiaotong Ji, Matthieu Zimmer, Sangwoong Yoon, Zhiyong Wang, Haitham Bou-Ammar, Aurélien Lucchi, Ilija Bogunovic
2026	J	`jnl`	OpenPyRo-A1: An Open Python-Based Low-Cost Bimanual Robot for Embodied AI. IEEE Robotics Autom. Lett. Helong Huang, Christopher E. Mower, Guowei Huang, Sarthak Das, Magnus Dierking, Guangyuan Luo, Kai Tan, Xi Chen, Yehai Yang, Yingbing Chen, Yiming Zeng, Yinchuan Li, Zhanpeng Zhang, Shuang Wu, Yingxue Zhang, Weichao Qiu, Tongtong Cao, Mian Qin, Sajjad Pakdamansavoji, Yuecheng Liu, Yuzheng Zhuang, Guangjian Tian, Jianye Hao, Jun Wang, Haitham Bou-Ammar, Xingyue Quan
2026	J	`jnl`	Scalable Power Sampling: Unlocking Efficient, Training-Free Reasoning for LLMs via Distribution Sharpening. CoRR Xiaotong Ji, Rasul Tutunov, Matthieu Zimmer, Haitham Bou-Ammar
2026	J	`jnl`	The Y-Combinator for LLMs: Solving Long-Context Rot with λ-Calculus. CoRR Amartya Roy, Rasul Tutunov, Xiaotong Ji, Matthieu Zimmer, Haitham Bou-Ammar
2026	J	`jnl`	Why the Brain Consolidates: Predictive Forgetting for Optimal Generalisation. CoRR Zafeirios Fountas, Adnan Oomerjee, Haitham Bou-Ammar, Jun Wang, Neil Burgess
2025	J	`jnl`	Al-Khwarizmi: Discovering Physical Laws with Foundation Models. CoRR Christopher E. Mower, Haitham Bou-Ammar
2025	J	`jnl`	Almost Surely Safe Alignment of Large Language Models at Inference-Time. CoRR Xiaotong Ji, Shyam Sundhar Ramesh, Matthieu Zimmer, Ilija Bogunovic, Jun Wang, Haitham Bou-Ammar
2025	J	`jnl`	Ark: An Open-source Python-based Framework for Robot Learning. CoRR Magnus Dierking, Christopher E. Mower, Sarthak Das, Helong Huang, Jiacheng Qiu, Cody Reading, Wei Chen, Huidong Liang, Guowei Huang, Jan Peters, Xingyue Quan, Jun Wang, Haitham Bou-Ammar
2025	J	`jnl`	Bottlenecked Transformers: Periodic KV Cache Abstraction for Generalised Reasoning. CoRR Adnan Oomerjee, Zafeirios Fountas, Zhongwei Yu, Haitham Bou-Ammar, Jun Wang
2025	J	`jnl`	Bourbaki: Self-Generated and Goal-Conditioned MDPs for Theorem Proving. CoRR Matthieu Zimmer, Xiaotong Ji, Rasul Tutunov, Anthony Bordg, Jun Wang, Haitham Bou-Ammar
2025	J	`jnl`	Data-driven Interpretable Hybrid Robot Dynamics. CoRR Christopher E. Mower, Rui Zong, Haitham Bou-Ammar
2025	A*	`conf`	Efficient Reinforcement Learning with Large Language Model Priors. ICLR Xue Yan, Yan Song, Xidong Feng, Mengyue Yang, Haifeng Zhang, Haitham Bou-Ammar, Jun Wang
2025	J	`jnl`	Embodied Arena: A Comprehensive, Unified, and Evolving Evaluation Platform for Embodied AI. CoRR Fei Ni, Min Zhang, Pengyi Li, Yifu Yuan, Lingfeng Zhang, Yuecheng Liu, Peilong Han, Longxin Kou, Shaojin Ma, Jinbin Qiao, David Gamaliel Arcos Bravo, Yuening Wang, Xiao Hu, Zhanguang Zhang, Xianze Yao, Yutong Li, Zhao Zhang, Ying Wen, Ying-Cong Chen, Xiaodan Liang, Liang Lin, Bin He, Haitham Bou-Ammar, He Wang, Huazhe Xu, Jiankang Deng, Shan Luo, Shuqiang Jiang, Wei Pan, Yang Gao, Stefanos Zafeiriou, Jan Peters, Yuzheng Zhuang, Yingxue Zhang, Yan Zheng, Hongyao Tang, Jianye Hao
2025	J	`jnl`	Experience is the Best Teacher: Grounding VLMs for Robotics through Self-Generated Memory. CoRR Guowei Lan, Kaixian Qu, René Zurbrügg, Changan Chen, Christopher E. Mower, Haitham Bou-Ammar, Marco Hutter
2025	A*	`conf`	Human-inspired Episodic Memory for Infinite Context LLMs. ICLR Zafeirios Fountas, Martin Benfeghoul, Adnan Oomerjee, Fenia Christopoulou, Gerasimos Lampouras, Haitham Bou-Ammar, Jun Wang
2025	J	`jnl`	Many of Your DPOs are Secretly One: Attempting Unification Through Mutual Information. CoRR Rasul Tutunov, Antoine Grosnit, Haitham Bou-Ammar
2025	A*	`conf`	Mixture of Attentions For Speculative Decoding. ICLR Matthieu Zimmer, Milan Gritta, Gerasimos Lampouras, Haitham Bou-Ammar, Jun Wang
2025	J	`jnl`	Model-Based and Sample-Efficient AI-Assisted Math Discovery in Sphere Packing. CoRR Rasul Tutunov, Alexandre Maraval, Antoine Grosnit, Xihan Li, Jun Wang, Haitham Bou-Ammar
2025	J	`jnl`	Rethinking Large Language Model Distillation: A Constrained Markov Decision Process Perspective. CoRR Matthieu Zimmer, Xiaotong Ji, Tu Nguyen, Haitham Bou-Ammar
2025	J	`jnl`	Safe Reinforcement Learning on the Constraint Manifold: Theory and Applications. IEEE Trans. Robotics Puze Liu, Haitham Bou-Ammar, Jan Peters, Davide Tateo
2025	—	`conf`	SparsePO: Controlling Preference Alignment of LLMs via Sparse Token Masks. EMNLP (Findings) Fenia Christopoulou, Ronald Cardenas, Gerasimos Lampouras, Haitham Bou-Ammar, Jun Wang
2025	J	`jnl`	SuRe: Surprise-Driven Prioritised Replay for Continual LLM Learning. CoRR Hugo Hazard, Zafeirios Fountas, Martin A. Benfeghoul, Adnan Oomerjee, Jun Wang, Haitham Bou-Ammar
2025	J	`jnl`	Subjective Depth and Timescale Transformers: Learning Where and When to Compute. CoRR Frederico Wieser, Martin Benfeghoul, Haitham Bou-Ammar, Jun Wang, Zafeirios Fountas
2025	J	`jnl`	Untangling Component Imbalance in Hybrid Linear Attention Conversion Methods. CoRR Martin Benfeghoul, Teresa Delgado, Adnan Oomerjee, Haitham Bou-Ammar, Jun Wang, Zafeirios Fountas
2024	A*	`conf`	A Retrospective on the Robot Air Hockey Challenge: Benchmarking Robust, Reliable, and Safe Learning Techniques for Real-world Robotics. NeurIPS Puze Liu, Jonas Günster, Niklas Funk, Simon Gröger, Dong Chen, Haitham Bou-Ammar, Julius Jankowski, Ante Maric, Sylvain Calinon, Andrej Orsula, Miguel S. Olivares-Méndez, Hongyi Zhou, Rudolf Lioutikov, Gerhard Neumann, Amarildo Likmeta, Amirhossein Zhalehmehrabi, Thomas Bonenfant, Marcello Restelli, Davide Tateo, Ziyuan Liu, Jan R. Peters
2024	J	`jnl`	A Retrospective on the Robot Air Hockey Challenge: Benchmarking Robust, Reliable, and Safe Learning Techniques for Real-world Robotics. CoRR Puze Liu, Jonas Guenster, Niklas Funk, Simon Gröger, Dong Chen, Haitham Bou-Ammar, Julius Jankowski, Ante Maric, Sylvain Calinon, Andrej Orsula, Miguel S. Olivares-Méndez, Hongyi Zhou, Rudolf Lioutikov, Gerhard Neumann, Amarildo Likmeta, Amirhossein Zhalehmehrabi, Thomas Bonenfant, Marcello Restelli, Davide Tateo, Ziyuan Liu, Jan Peters
2024	J	`jnl`	Bayesian Reward Models for LLM Alignment. CoRR Adam X. Yang, Maxime Robeyns, Thomas Coste, Jun Wang, Haitham Bou-Ammar, Laurence Aitchison
2024	J	`jnl`	Efficient Reinforcement Learning with Large Language Model Priors. CoRR Xue Yan, Yan Song, Xidong Feng, Mengyue Yang, Haifeng Zhang, Haitham Bou-Ammar, Jun Wang
2024	J	`jnl`	Fast Kinodynamic Planning on the Constraint Manifold With Deep Neural Networks. IEEE Trans. Robotics Piotr Kicki, Puze Liu, Davide Tateo, Haitham Bou-Ammar, Krzysztof Walas, Piotr Skrzypczynski, Jan Peters
2024	A*	`conf`	Group Robust Preference Optimization in Reward-free RLHF. NeurIPS Shyam Sundhar Ramesh, Yifan Hu, Iason Chaimalas, Viraj Mehta, Pier Giuseppe Sessa, Haitham Bou-Ammar, Ilija Bogunovic
2024	J	`jnl`	Group Robust Preference Optimization in Reward-free RLHF. CoRR Shyam Sundhar Ramesh, Yifan Hu, Iason Chaimalas, Viraj Mehta, Pier Giuseppe Sessa, Haitham Bou-Ammar, Ilija Bogunovic
2024	J	`jnl`	Human-like Episodic Memory for Infinite Context LLMs. CoRR Zafeirios Fountas, Martin Benfeghoul, Adnan Oomerjee, Fenia Christopoulou, Gerasimos Lampouras, Haitham Bou-Ammar, Jun Wang
2024	J	`jnl`	Large Language Models Orchestrating Structured Reasoning Achieve Kaggle Grandmaster Level. CoRR Antoine Grosnit, Alexandre Maraval, James Doran, Giuseppe Paolo, Albert Thomas, Refinath Shahul Hameed Nabeezath Beevi, Jonas Gonzalez, Khyati Khandelwal, Ignacio Iacobacci, Abdelhakim Benechehab, Hamza Cherkaoui, Youssef Attia El Hili, Kun Shao, Jianye Hao, Jun Yao, Balázs Kégl, Haitham Bou-Ammar, Jun Wang
2024	A*	`conf`	Measures of diversity and space-filling designs for categorical data. ICML Cédric Malherbe, Emilio Domínguez-Sánchez, Merwan Barlier, Igor Colin, Haitham Bou-Ammar, Tom Diethe
2024	J	`jnl`	Mixture of Attentions For Speculative Decoding. CoRR Matthieu Zimmer, Milan Gritta, Gerasimos Lampouras, Haitham Bou-Ammar, Jun Wang
2024	J	`jnl`	ROS-LLM: A ROS framework for embodied AI with task feedback and structured reasoning. CoRR Christopher E. Mower, Yuhui Wan, Hongzhan Yu, Antoine Grosnit, Jonas Gonzalez-Billandon, Matthieu Zimmer, Jinlong Wang, Xinyu Zhang, Yao Zhao, Anbang Zhai, Puze Liu, Davide Tateo, Cesar Cadena, Marco Hutter, Jan Peters, Guangjian Tian, Yuzheng Zhuang, Kun Shao, Xingyue Quan, Jianye Hao, Jun Wang, Haitham Bou-Ammar
2024	J	`jnl`	Safe Reinforcement Learning on the Constraint Manifold: Theory and Applications. CoRR Puze Liu, Haitham Bou-Ammar, Jan Peters, Davide Tateo
2024	J	`jnl`	ShortCircuit: AlphaZero-Driven Circuit Design. CoRR Dimitrios Tsaras, Antoine Grosnit, Lei Chen, Zhiyao Xie, Haitham Bou-Ammar, Mingxuan Yuan
2024	J	`jnl`	SparsePO: Controlling Preference Alignment of LLMs via Sparse Token Masks. CoRR Fenia Christopoulou, Ronald Cardenas, Gerasimos Lampouras, Haitham Bou-Ammar, Jun Wang
2024	J	`jnl`	ZSL-RPPO: Zero-Shot Learning for Quadrupedal Locomotion in Challenging Terrains using Recurrent Proximal Policy Optimization. CoRR Yao Zhao, Tao Wu, Yijie Zhu, Xiang Lu, Jun Wang, Haitham Bou-Ammar, Xinyu Zhang, Peng Du
2023	A*	`conf`	Are Random Decompositions all we need in High Dimensional Bayesian Optimisation? ICML Juliusz Krysztof Ziomek, Haitham Bou-Ammar
2023	J	`jnl`	Are Random Decompositions all we need in High Dimensional Bayesian Optimisation? CoRR Juliusz Ziomek, Haitham Bou-Ammar
2023	J	`jnl`	Contextual Causal Bayesian Optimisation. CoRR Vahan Arsenyan, Antoine Grosnit, Haitham Bou-Ammar
2023	A*	`conf`	End-to-End Meta-Bayesian Optimisation with Transformer Neural Processes. NeurIPS Alexandre Maraval, Matthieu Zimmer, Antoine Grosnit, Haitham Bou-Ammar
2023	J	`jnl`	End-to-End Meta-Bayesian Optimisation with Transformer Neural Processes. CoRR Alexandre Maraval, Matthieu Zimmer, Antoine Grosnit, Haitham Bou-Ammar
2023	J	`jnl`	Fast Kinodynamic Planning on the Constraint Manifold with Deep Neural Networks. CoRR Piotr Kicki, Puze Liu, Davide Tateo, Haitham Bou-Ammar, Krzysztof Walas, Piotr Skrzypczynski, Jan Peters
2023	A*	`conf`	Framework and Benchmarks for Combinatorial and Mixed-variable Bayesian Optimization. NeurIPS Kamil Dreczkowski, Antoine Grosnit, Haitham Bou-Ammar
2023	J	`jnl`	Framework and Benchmarks for Combinatorial and Mixed-variable Bayesian Optimization. CoRR Kamil Dreczkowski, Antoine Grosnit, Haitham Bou-Ammar
2023	A*	`conf`	Lightweight Structural Choices Operator for Technology Mapping. DAC Antoine Grosnit, Matthieu Zimmer, Rasul Tutunov, Xing Li, Lei Chen, Fan Yang, Mingxuan Yuan, Haitham Bou-Ammar
2023	A*	`conf`	Online PCA in Converging Self-consistent Field Equations. NeurIPS Xihan Li, Xiang Chen, Rasul Tutunov, Haitham Bou-Ammar, Lei Wang, Jun Wang
2023	J	`jnl`	Pangu-Agent: A Fine-Tunable Generalist Agent with Structured Reasoning. CoRR Filippos Christianos, Georgios Papoudakis, Matthieu Zimmer, Thomas Coste, Zhihao Wu, Jingxuan Chen, Khyati Khandelwal, James Doran, Xidong Feng, Jiacheng Liu, Zheng Xiong, Yicheng Luo, Jianye Hao, Kun Shao, Haitham Bou-Ammar, Jun Wang
2023	A*	`conf`	Reinforcement Learning for Safe Robot Control using Control Lyapunov Barrier Functions. ICRA Desong Du, Shaohang Han, Naiming Qi, Haitham Bou-Ammar, Jun Wang, Wei Pan
2023	J	`jnl`	Reinforcement Learning for Safe Robot Control using Control Lyapunov Barrier Functions. CoRR Desong Du, Shaohang Han, Naiming Qi, Haitham Bou-Ammar, Jun Wang, Wei Pan
2023	J	`jnl`	Why Can Large Language Models Generate Correct Chain-of-Thoughts? CoRR Rasul Tutunov, Antoine Grosnit, Juliusz Ziomek, Jun Wang, Haitham Bou-Ammar
2022	J	`jnl`	AntBO: Towards Real-World Automated Antibody Design with Combinatorial Bayesian Optimisation. CoRR Mohammad Asif Khan, Alexander I. Cowen-Rivers, Derrick-Goh-Xin Deik, Antoine Grosnit, Kamil Dreczkowski, Philippe A. Robert, Victor Greiff, Rasul Tutunov, Dany Bou-Ammar, Jun Wang, Haitham Bou-Ammar
2022	A	`conf`	BOiLS: Bayesian Optimisation for Logic Synthesis. DATE Antoine Grosnit, Cédric Malherbe, Rasul Tutunov, Xingchen Wan, Jun Wang, Haitham Bou-Ammar
2022	A*	`conf`	Enhancing Safe Exploration Using Safety State Augmentation. NeurIPS Aivar Sootla, Alexander I. Cowen-Rivers, Jun Wang, Haitham Bou-Ammar
2022	J	`jnl`	Enhancing Safe Exploration Using Safety State Augmentation. CoRR Aivar Sootla, Alexander I. Cowen-Rivers, Jun Wang, Haitham Bou-Ammar
2022	J	`jnl`	HEBO: An Empirical Study of Assumptions in Bayesian Optimisation. J. Artif. Intell. Res. Alexander I. Cowen-Rivers, Wenlong Lyu, Rasul Tutunov, Zhi Wang, Antoine Grosnit, Ryan-Rhys Griffiths, Alexandre Max Maraval, Jianye Hao, Jun Wang, Jan Peters, Haitham Bou-Ammar
2022	J	`jnl`	Learning Geometric Constraints in Task and Motion Planning. CoRR Tianyu Ren, Alexander Imani Cowen-Rivers, Haitham Bou-Ammar, Jan Peters
2022	J	`jnl`	Online Double Oracle. Trans. Mach. Learn. Res. Le Cong Dinh, Stephen Marcus McAleer, Zheng Tian, Nicolas Perez Nieves, Oliver Slumbers, David Henry Mguni, Jun Wang, Haitham Bou-Ammar, Yaodong Yang
2022	A*	`conf`	Optimistic Tree Searches for Combinatorial Black-Box Optimization. NeurIPS Cédric Malherbe, Antoine Grosnit, Rasul Tutunov, Haitham Bou-Ammar, Jun Wang
2022	A*	`conf`	Reinforcement Learning in Presence of Discrete Markovian Context Evolution. ICLR Hang Ren, Aivar Sootla, Taher Jafferjee, Junxiao Shen, Jun Wang, Haitham Bou-Ammar
2022	J	`jnl`	Reinforcement Learning in Presence of Discrete Markovian Context Evolution. CoRR Hang Ren, Aivar Sootla, Taher Jafferjee, Junxiao Shen, Jun Wang, Haitham Bou-Ammar
2022	J	`jnl`	SAMBA: safe model-based & active reinforcement learning. Mach. Learn. Alexander I. Cowen-Rivers, Daniel Palenicek, Vincent Moens, Mohammed Amin Abdullah, Aivar Sootla, Jun Wang, Haitham Bou-Ammar
2022	J	`jnl`	SAUTE RL: Almost Surely Safe Reinforcement Learning Using State Augmentation. CoRR Aivar Sootla, Alexander I. Cowen-Rivers, Taher Jafferjee, Ziyan Wang, David Mguni, Jun Wang, Haitham Bou-Ammar
2022	J	`jnl`	Sample-Efficient Optimisation with Probabilistic Transformer Surrogates. CoRR Alexandre Maraval, Matthieu Zimmer, Antoine Grosnit, Rasul Tutunov, Jun Wang, Haitham Bou-Ammar
2022	J	`jnl`	Self-consistent Gradient-like Eigen Decomposition in Solving Schrödinger Equations. CoRR Xihan Li, Xiang Chen, Rasul Tutunov, Haitham Bou-Ammar, Lei Wang, Jun Wang
2022	J	`jnl`	Structured Q-learning For Antibody Design. CoRR Alexander I. Cowen-Rivers, Philip John Gorinski, Aivar Sootla, Asif Khan, Furui Liu, Jun Wang, Jan Peters, Haitham Bou-Ammar
2021	J	`jnl`	Are We Forgetting about Compositional Optimisers in Bayesian Optimisation? J. Mach. Learn. Res. Antoine Grosnit, Alexander I. Cowen-Rivers, Rasul Tutunov, Ryan-Rhys Griffiths, Jun Wang, Haitham Bou-Ammar
2021	J	`jnl`	BOiLS: Bayesian Optimisation for Logic Synthesis. CoRR Antoine Grosnit, Cédric Malherbe, Rasul Tutunov, Xingchen Wan, Jun Wang, Haitham Bou-Ammar
2021	A	`conf`	Diverse Auto-Curriculum is Critical for Successful Real-World Multiagent Learning Systems. AAMAS Yaodong Yang, Jun Luo, Ying Wen, Oliver Slumbers, Daniel Graves, Haitham Bou-Ammar, Jun Wang, Matthew E. Taylor
2021	J	`jnl`	Diverse Auto-Curriculum is Critical for Successful Real-World Multiagent Learning Systems. CoRR Yaodong Yang, Jun Luo, Ying Wen, Oliver Slumbers, Daniel Graves, Haitham Bou-Ammar, Jun Wang, Matthew E. Taylor
2021	A	`conf`	Efficient and Reactive Planning for High Speed Robot Air Hockey. IROS Puze Liu, Davide Tateo, Haitham Bou-Ammar, Jan Peters
2021	J	`jnl`	Efficient and Reactive Planning for High Speed Robot Air Hockey. CoRR Puze Liu, Davide Tateo, Haitham Bou-Ammar, Jan Peters
2021	J	`jnl`	High-Dimensional Bayesian Optimisation with Variational Autoencoders and Deep Metric Learning. CoRR Antoine Grosnit, Rasul Tutunov, Alexandre Max Maraval, Ryan-Rhys Griffiths, Alexander I. Cowen-Rivers, Lin Yang, Lin Zhu, Wenlong Lyu, Zhitang Chen, Jun Wang, Jan Peters, Haitham Bou-Ammar
2021	J	`jnl`	Implicit Variational Conditional Sampling with Normalizing Flows. CoRR Vincent Moens, Aivar Sootla, Haitham Bou-Ammar, Jun Wang
2021	J	`jnl`	Online Double Oracle. CoRR Le Cong Dinh, Yaodong Yang, Zheng Tian, Nicolas Perez Nieves, Oliver Slumbers, David Henry Mguni, Haitham Bou-Ammar, Jun Wang
2021	Misc	`conf`	Robot Reinforcement Learning on the Constraint Manifold. CoRL Puze Liu, Davide Tateo, Haitham Bou-Ammar, Jan Peters
2020	J	`jnl`	Are we Forgetting about Compositional Optimisers in Bayesian Optimisation? CoRR Antoine Grosnit, Alexander I. Cowen-Rivers, Rasul Tutunov, Ryan-Rhys Griffiths, Jun Wang, Haitham Bou-Ammar
2020	J	`jnl`	Compositional ADAM: An Adaptive Compositional Solver. CoRR Rasul Tutunov, Minne Li, Jun Wang, Haitham Bou-Ammar
2020	J	`jnl`	HEBO: Heteroscedastic Evolutionary Bayesian Optimisation. CoRR Alexander I. Cowen-Rivers, Wenlong Lyu, Zhi Wang, Rasul Tutunov, Jianye Hao, Jun Wang, Haitham Bou-Ammar
2020	A*	`conf`	Learning to Communicate Implicitly by Actions. AAAI Zheng Tian, Shihao Zou, Ian Davies, Tim Warr, Lisheng Wu, Haitham Bou-Ammar, Jun Wang
2020	J	`jnl`	SMARTS: Scalable Multi-Agent Reinforcement Learning Training School for Autonomous Driving. CoRR Ming Zhou, Jun Luo, Julian Villela, Yaodong Yang, David Rusu, Jiayu Miao, Weinan Zhang, Montgomery Alban, Iman Fadakar, Zheng Chen, Aurora Chongxi Huang, Ying Wen, Kimia Hassanzadeh, Daniel Graves, Dong Chen, Zhengbang Zhu, Nhat M. Nguyen, Mohamed Elsayed, Kun Shao, Sanjeevan Ahilan, Baokuan Zhang, Jiannan Wu, Zhengang Fu, Kasra Rezaee, Peyman Yadmellat, Mohsen Rohani, Nicolas Perez Nieves, Yihan Ni, Seyedershad Banijamali, Alexander I. Cowen-Rivers, Zheng Tian, Daniel Palenicek, Haitham Bou-Ammar, Hongbo Zhang, Wulong Liu, Jianye Hao, Jun Wang
2020	A	`conf`	αα-Rank: Practically Scaling α-Rank through Stochastic Optimisation. AAMAS Yaodong Yang, Rasul Tutunov, Phu Sakulwongtana, Haitham Bou-Ammar
2019	J	`jnl`	Derivative-Free & Order-Robust Optimisation. CoRR Victor Gabillon, Rasul Tutunov, Michal Valko, Haitham Bou-Ammar
2019	J	`jnl`	Distributed Newton Method for Large-Scale Consensus Optimization. IEEE Trans. Autom. Control. Rasul Tutunov, Haitham Bou-Ammar, Ali Jadbabaie
2019	A*	`conf`	Multi-View Reinforcement Learning. NeurIPS Minne Li, Lisheng Wu, Jun Wang, Haitham Bou-Ammar
2019	J	`jnl`	Multi-View Reinforcement Learning. CoRR Minne Li, Lisheng Wu, Haitham Bou-Ammar, Jun Wang
2019	J	`jnl`	Wasserstein Robust Reinforcement Learning. CoRR Mohammed Amin Abdullah, Hang Ren, Haitham Bou-Ammar, Vladimir Milenkovic, Rui Luo, Mingtian Zhang, Jun Wang
2018	A*	`conf`	Balancing Two-Player Stochastic Games with Soft Q-Learning. IJCAI Jordi Grau-Moya, Felix Leibfried, Haitham Bou-Ammar
2018	J	`jnl`	Balancing Two-Player Stochastic Games with Soft Q-Learning. CoRR Jordi Grau-Moya, Felix Leibfried, Haitham Bou-Ammar
2018	A*	`conf`	Distributed Multitask Reinforcement Learning with Quadratic Convergence. NeurIPS Rasul Tutunov, Dongho Kim, Haitham Bou-Ammar
2018	J	`jnl`	Learning High-level Representations from Demonstrations. CoRR Garrett Andersen, Peter Vrancx, Haitham Bou-Ammar
2018	J	`jnl`	Model-Based Stabilisation of Deep Reinforcement Learning. CoRR Felix Leibfried, Rasul Tutunov, Peter Vrancx, Haitham Bou-Ammar
2018	J	`jnl`	Reports on the 2018 AAAI Spring Symposium Series. AI Mag. Christopher Amato, Haitham Bou-Ammar, Elizabeth F. Churchill, Erez Karpas, Takashi Kido, Mike Kuniavsky, William F. Lawless, Francesca Rossi, Frans A. Oliehoek, Stephen Russell, Keiki Takadama, Siddharth Srivastava, Karl Tuyls, Philip van Allen, K. Brent Venable, Peter Vrancx, Shiqi Zhang
2017	J	`jnl`	An Information-Theoretic Optimality Principle for Deep Reinforcement Learning. CoRR Felix Leibfried, Jordi Grau-Moya, Haitham Bou-Ammar
2017	—	`conf`	Correctness-by-Learning of Infinite-State Component-Based Systems. FACS Haitham Bou-Ammar, Mohamad Jaber, Mohamed Nassar
2017	—	`conf`	Distributed lifelong reinforcement learning with sub-linear regret. CDC Rasul Tutunov, Julia El Zini, Haitham Bou-Ammar, Ali Jadbabaie
2017	J	`jnl`	Estimating 3D trajectories from 2D projections via disjunctive factored four-way conditional restricted Boltzmann machines. Pattern Recognit. Decebal Constantin Mocanu, Haitham Bou-Ammar, Luis Puig, Eric Eaton, Antonio Liotta
2017	J	`jnl`	Nonconvex Policy Search Using Variational Inequalities. Neural Comput. Yusen Zhan, Haitham Bou-Ammar, Matthew E. Taylor
2017	A*	`conf`	Scalable Multitask Policy Gradient Reinforcement Learning. AAAI Salam El Bsat, Haitham Bou-Ammar, Matthew E. Taylor
2017	J	`jnl`	Scalable lifelong reinforcement learning. Pattern Recognit. Yusen Zhan, Haitham Bou-Ammar, Matthew E. Taylor
2016	J	`jnl`	A Distributed Newton Method for Large Scale Consensus Optimization. CoRR Rasul Tutunov, Haitham Bou-Ammar, Ali Jadbabaie
2016	—	`conf`	An exact distributed newton method for reinforcement learning. CDC Rasul Tutunov, Haitham Bou-Ammar, Ali Jadbabaie
2016	J	`jnl`	Estimating 3D Trajectories from 2D Projections via Disjunctive Factored Four-Way Conditional Restricted Boltzmann Machines. CoRR Decebal Constantin Mocanu, Haitham Bou-Ammar, Luis Puig, Eric Eaton, Antonio Liotta
2016	J	`jnl`	On the prevalence of hierarchies in social networks. Soc. Netw. Anal. Min. Bijan Ranjbar Sahraei, Haitham Bou-Ammar, Karl Tuyls, Gerhard Weiss
2016	A*	`conf`	Theoretically-Grounded Policy Advice from Multiple Teachers in Reinforcement Learning Settings with Applications to Negative Transfer. IJCAI Yusen Zhan, Haitham Bou-Ammar, Matthew E. Taylor
2016	J	`jnl`	Theoretically-Grounded Policy Advice from Multiple Teachers in Reinforcement Learning Settings with Applications to Negative Transfer. CoRR Yusen Zhan, Haitham Bou-Ammar, Matthew E. Taylor
2015	J	`jnl`	A Fast Distributed Solver for Symmetric Diagonally Dominant Linear Equations. CoRR Rasul Tutunov, Haitham Bou-Ammar, Ali Jadbabaie
2015	A*	`conf`	Autonomous Cross-Domain Knowledge Transfer in Lifelong Policy Gradient Reinforcement Learning. IJCAI Haitham Bou-Ammar, Eric Eaton, José-Marcio Luna, Paul Ruvolo
2015	J	`jnl`	Factored four way conditional restricted Boltzmann machines for activity recognition. Pattern Recognit. Lett. Decebal Constantin Mocanu, Haitham Bou-Ammar, Dietwig Lowet, Kurt Driessens, Antonio Liotta, Gerhard Weiss, Karl Tuyls
2015	—	`conf`	Fast, accurate second order methods for network optimization. CDC Rasul Tutunov, Haitham Bou-Ammar, Ali Jadbabaie
2015	B	`conf`	On the Skewed Degree Distribution of Hierarchical Networks. ASONAM Bijan Ranjbar Sahraei, Haitham Bou-Ammar, Karl Tuyls, Gerhard Weiss
2015	B	`conf`	Reduced reference image quality assessment via Boltzmann Machines. IM Decebal Constantin Mocanu, Georgios Exarchakos, Haitham Bou-Ammar, Antonio Liotta
2015	A*	`conf`	Safe Policy Search for Lifelong Reinforcement Learning with Sublinear Regret. ICML Haitham Bou-Ammar, Rasul Tutunov, Eric Eaton
2015	J	`jnl`	Safe Policy Search for Lifelong Reinforcement Learning with Sublinear Regret. CoRR Haitham Bou-Ammar, Rasul Tutunov, Eric Eaton
2015	A*	`conf`	Unsupervised Cross-Domain Transfer in Policy Gradient Reinforcement Learning via Manifold Alignment. AAAI Haitham Bou-Ammar, Eric Eaton, Paul Ruvolo, Matthew E. Taylor
2014	J	`jnl`	Automated Transfer for Reinforcement Learning Tasks. Künstliche Intell. Haitham Bou-Ammar, Siqi Chen, Karl Tuyls, Gerhard Weiss
2014	A	`conf`	Evolution of cooperation in arbitrary complex networks. AAMAS Bijan Ranjbar Sahraei, Haitham Bou-Ammar, Daan Bloembergen, Karl Tuyls, Gerhard Weiss
2014	B	`conf`	Inexpensive user tracking using Boltzmann Machines. SMC Elena Mocanu, Decebal Constantin Mocanu, Haitham Bou-Ammar, Zoran Zivkovic, Antonio Liotta, Evgueni N. Smirnov
2014	A	`conf`	Influencing Social Networks: An Optimal Control Study. ECAI Daan Bloembergen, Bijan Ranjbar Sahraei, Haitham Bou-Ammar, Karl Tuyls, Gerhard Weiss
2014	J	`jnl`	On the Degree Distribution of Pólya Urn Graph Processes. CoRR Rasul Tutunov, Haitham Bou-Ammar, Ali Jadbabaie, Eric Eaton
2014	A*	`conf`	Online Multi-Task Gradient Temporal-Difference Learning. AAAI Vishnu Purushothaman Sreenivasan, Haitham Bou-Ammar, Eric Eaton
2014	A*	`conf`	Online Multi-Task Learning for Policy Gradient Methods. ICML Haitham Bou-Ammar, Eric Eaton, Paul Ruvolo, Matthew E. Taylor
2014	A*	`conf`	Theory of Cooperation in Complex Social Networks. AAAI Bijan Ranjbar Sahraei, Haitham Bou-Ammar, Daan Bloembergen, Karl Tuyls, Gerhard Weiss
2014	J	`jnl`	Transfer for Automated Negotiation. Künstliche Intell. Siqi Chen, Haitham Bou-Ammar, Karl Tuyls, Gerhard Weiss
2013	—	`conf`	Automatically Mapped Transfer between Reinforcement Learning Tasks via Three-Way Restricted Boltzmann Machines. ECML/PKDD (2) Haitham Bou-Ammar, Decebal Constantin Mocanu, Matthew E. Taylor, Kurt Driessens, Karl Tuyls, Gerhard Weiss
2013	A*	`conf`	Conditional Restricted Boltzmann Machines for Negotiations in Highly Competitive and Complex Domains. IJCAI Siqi Chen, Haitham Bou-Ammar, Karl Tuyls, Gerhard Weiss
2013	Misc	`conf`	Conformity-Based Transfer AdaBoost Algorithm. AIAI Shuang Zhou, Evgueni N. Smirnov, Haitham Bou-Ammar, Ralf Peeters
2013	A	`conf`	Optimizing complex automated negotiation using sparse pseudo-input gaussian processes. AAMAS Siqi Chen, Haitham Bou-Ammar, Karl Tuyls, Gerhard Weiss
2013	—	`conf`	Swarm-based evaluation of nonparametric SysML mechatronics system design. ICM Mohammad Chami, Haitham Bou-Ammar, Holger Voos, Karl Tuyls, Gerhard Weiss
2012	—	`conf`	Evolutionary Dynamics of Ant Colony Optimization. MATES Haitham Bou-Ammar, Karl Tuyls, Michael Kaisers
2012	A	`conf`	Reinforcement learning transfer via sparse coding. AAMAS Haitham Bou-Ammar, Karl Tuyls, Matthew E. Taylor, Kurt Driessens, Gerhard Weiss
2011	C	`conf`	Reinforcement Learning Transfer Using a Sparse Coded Inter-task Mapping. EUMAS Haitham Bou-Ammar, Matthew E. Taylor, Karl Tuyls, Gerhard Weiss
2011	—	`conf`	Reinforcement Learning Transfer via Common Subspaces. ALA Haitham Bou-Ammar, Matthew E. Taylor
2010	C	`conf`	Controller Design for Quadrotor UAVs using Reinforcement Learning. CCA Haitham Bou-Ammar, Holger Voos, Wolfgang Ertel
2010	C	`conf`	Nonlinear Tracking and Landing Controller for Quadrotor Aerial Robots. CCA Holger Voos, Haitham Bou-Ammar