Search Results for author: Haitham Bou Ammar

Found 21 papers, 7 papers with code

Framework and Benchmarks for Combinatorial and Mixed-variable Bayesian Optimization

1 code implementation NeurIPS 2023 Kamil Dreczkowski, Antoine Grosnit, Haitham Bou Ammar

This paper introduces a modular framework for Mixed-variable and Combinatorial Bayesian Optimization (MCBO) to address the lack of systematic benchmarking and standardized evaluation in the field.

Bayesian Optimization Benchmarking

Effects of Safety State Augmentation on Safe Exploration

1 code implementation6 Jun 2022 Aivar Sootla, Alexander I. Cowen-Rivers, Jun Wang, Haitham Bou Ammar

We further show that Simmer can stabilize training and improve the performance of safe RL with average constraints.

Reinforcement Learning (RL) Safe Exploration +1

Sample-Efficient Optimisation with Probabilistic Transformer Surrogates

no code implementations27 May 2022 Alexandre Maraval, Matthieu Zimmer, Antoine Grosnit, Rasul Tutunov, Jun Wang, Haitham Bou Ammar

First, we notice that these models are trained on uniformly distributed inputs, which impairs predictive accuracy on non-uniform data - a setting arising from any typical BO loop due to exploration-exploitation trade-offs.

Bayesian Optimisation Gaussian Processes

BOiLS: Bayesian Optimisation for Logic Synthesis

no code implementations11 Nov 2021 Antoine Grosnit, Cedric Malherbe, Rasul Tutunov, Xingchen Wan, Jun Wang, Haitham Bou Ammar

Optimising the quality-of-results (QoR) of circuits during logic synthesis is a formidable challenge necessitating the exploration of exponentially sized search spaces.

Bayesian Optimisation Navigate

Viscos Flows: Variational Schur Conditional Sampling With Normalizing Flows

no code implementations6 Jul 2021 Vincent Moens, Aivar Sootla, Haitham Bou Ammar, Jun Wang

We present a method for conditional sampling for pre-trained normalizing flows when only part of an observation is available.

Online Double Oracle

1 code implementation13 Mar 2021 Le Cong Dinh, Yaodong Yang, Stephen Mcaleer, Zheng Tian, Nicolas Perez Nieves, Oliver Slumbers, David Henry Mguni, Haitham Bou Ammar, Jun Wang

Solving strategic games with huge action space is a critical yet under-explored topic in economics, operations research and artificial intelligence.

Multi-View Reinforcement Learning

1 code implementation NeurIPS 2019 Minne Li, Lisheng Wu, Haitham Bou Ammar, Jun Wang

This paper is concerned with multi-view reinforcement learning (MVRL), which allows for decision making when agents share common dynamics but adhere to different observation models.

Decision Making reinforcement-learning +1

Derivative-Free & Order-Robust Optimisation

no code implementations9 Oct 2019 Victor Gabillon, Rasul Tutunov, Michal Valko, Haitham Bou Ammar

In this paper, we formalise order-robust optimisation as an instance of online learning minimising simple regret, and propose Vroom, a zero'th order optimisation algorithm capable of achieving vanishing regret in non-stationary environments, while recovering favorable rates under stochastic reward-generating processes.

$α^α$-Rank: Practically Scaling $α$-Rank through Stochastic Optimisation

no code implementations25 Sep 2019 Yaodong Yang, Rasul Tutunov, Phu Sakulwongtana, Haitham Bou Ammar

Furthermore, we also show successful results on large joint strategy profiles with a maximum size in the order of $\mathcal{O}(2^{25})$ ($\approx 33$ million joint strategies) -- a setting not evaluable using $\alpha$-Rank with reasonable computational budget.

Stochastic Optimization

Wasserstein Robust Reinforcement Learning

no code implementations30 Jul 2019 Mohammed Amin Abdullah, Hang Ren, Haitham Bou Ammar, Vladimir Milenkovic, Rui Luo, Mingtian Zhang, Jun Wang

Reinforcement learning algorithms, though successful, tend to over-fit to training environments hampering their application to the real-world.

reinforcement-learning Reinforcement Learning (RL)

Learning to Communicate Implicitly By Actions

no code implementations10 Oct 2018 Zheng Tian, Shihao Zou, Ian Davies, Tim Warr, Lisheng Wu, Haitham Bou Ammar, Jun Wang

The auxiliary reward for communication is integrated into the learning of the policy module.

Estimating 3D Trajectories from 2D Projections via Disjunctive Factored Four-Way Conditional Restricted Boltzmann Machines

no code implementations20 Apr 2016 Decebal Constantin Mocanu, Haitham Bou Ammar, Luis Puig, Eric Eaton, Antonio Liotta

Estimation, recognition, and near-future prediction of 3D trajectories based on their two dimensional projections available from one camera source is an exceptionally difficult problem due to uncertainty in the trajectories and environment, high dimensionality of the specific trajectory states, lack of enough labeled data and so on.

Future prediction Time Series +1

Theoretically-Grounded Policy Advice from Multiple Teachers in Reinforcement Learning Settings with Applications to Negative Transfer

no code implementations13 Apr 2016 Yusen Zhan, Haitham Bou Ammar, Matthew E. Taylor

This paper formally defines a setting where multiple teacher agents can provide advice to a student and introduces an algorithm to leverage both autonomous exploration and teacher's advice.

reinforcement-learning Reinforcement Learning (RL) +1

Safe Policy Search for Lifelong Reinforcement Learning with Sublinear Regret

no code implementations21 May 2015 Haitham Bou Ammar, Rasul Tutunov, Eric Eaton

Lifelong reinforcement learning provides a promising framework for developing versatile agents that can accumulate knowledge over a lifetime of experience and rapidly learn new tasks by building upon prior knowledge.

reinforcement-learning Reinforcement Learning (RL)

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