Search Results for author: Daniel Mankowitz

Found 7 papers, 4 papers with code

Transformers Meet Directed Graphs

1 code implementation31 Jan 2023 Simon Geisler, Yujia Li, Daniel Mankowitz, Ali Taylan Cemgil, Stephan Günnemann, Cosmin Paduraru

Transformers were originally proposed as a sequence-to-sequence model for text but have become vital for a wide range of modalities, including images, audio, video, and undirected graphs.

graph construction Graph Property Prediction

Local Search for Policy Iteration in Continuous Control

no code implementations12 Oct 2020 Jost Tobias Springenberg, Nicolas Heess, Daniel Mankowitz, Josh Merel, Arunkumar Byravan, Abbas Abdolmaleki, Jackie Kay, Jonas Degrave, Julian Schrittwieser, Yuval Tassa, Jonas Buchli, Dan Belov, Martin Riedmiller

We demonstrate that additional computation spent on model-based policy improvement during learning can improve data efficiency, and confirm that model-based policy improvement during action selection can also be beneficial.

Continuous Control Reinforcement Learning (RL)

RL Unplugged: A Suite of Benchmarks for Offline Reinforcement Learning

2 code implementations24 Jun 2020 Caglar Gulcehre, Ziyu Wang, Alexander Novikov, Tom Le Paine, Sergio Gomez Colmenarejo, Konrad Zolna, Rishabh Agarwal, Josh Merel, Daniel Mankowitz, Cosmin Paduraru, Gabriel Dulac-Arnold, Jerry Li, Mohammad Norouzi, Matt Hoffman, Ofir Nachum, George Tucker, Nicolas Heess, Nando de Freitas

We hope that our suite of benchmarks will increase the reproducibility of experiments and make it possible to study challenging tasks with a limited computational budget, thus making RL research both more systematic and more accessible across the community.

Atari Games DQN Replay Dataset +3

A Bayesian Approach to Robust Reinforcement Learning

no code implementations20 May 2019 Esther Derman, Daniel Mankowitz, Timothy Mann, Shie Mannor

Robust Markov Decision Processes (RMDPs) intend to ensure robustness with respect to changing or adversarial system behavior.

reinforcement-learning Reinforcement Learning (RL) +1

Challenges of Real-World Reinforcement Learning

1 code implementation29 Apr 2019 Gabriel Dulac-Arnold, Daniel Mankowitz, Todd Hester

Reinforcement learning (RL) has proven its worth in a series of artificial domains, and is beginning to show some successes in real-world scenarios.

reinforcement-learning Reinforcement Learning (RL)

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