no code implementations • 30 Nov 2023 • Kale-ab Tessera, Callum Rhys Tilbury, Sasha Abramowitz, Ruan de Kock, Omayma Mahjoub, Benjamin Rosman, Sara Hooker, Arnu Pretorius
Optimising deep neural networks is a challenging task due to complex training dynamics, high computational requirements, and long training times.
1 code implementation • 16 Jun 2023 • Clément Bonnet, Daniel Luo, Donal Byrne, Shikha Surana, Sasha Abramowitz, Paul Duckworth, Vincent Coyette, Laurence I. Midgley, Elshadai Tegegn, Tristan Kalloniatis, Omayma Mahjoub, Matthew Macfarlane, Andries P. Smit, Nathan Grinsztajn, Raphael Boige, Cemlyn N. Waters, Mohamed A. Mimouni, Ulrich A. Mbou Sob, Ruan de Kock, Siddarth Singh, Daniel Furelos-Blanco, Victor Le, Arnu Pretorius, Alexandre Laterre
Open-source reinforcement learning (RL) environments have played a crucial role in driving progress in the development of AI algorithms.
no code implementations • 29 Sep 2021 • Sasha Abramowitz
This paper investigates the performance of Scalable Evolution Strategies (S-ES) as a Hierarchical Reinforcement Learning (HRL) approach.
Hierarchical Reinforcement Learning Policy Gradient Methods +2
1 code implementation • 3 Jul 2021 • Ruan de Kock, Omayma Mahjoub, Sasha Abramowitz, Wiem Khlifi, Callum Rhys Tilbury, Claude Formanek, Andries Smit, Arnu Pretorius
Our criteria for such software is that it should be simple enough to use to implement new ideas quickly, while at the same time be scalable and fast enough to test those ideas in a reasonable amount of time.