1.1k citations · 5k across the 117 of their papers we have counts for
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LipNet: End-to-End Sentence-level Lipreading
Yannis M. Assael, Brendan Shillingford, Shimon Whiteson +1
Lipreading is the task of decoding text from the movement of a speaker's mouth. Traditional approaches separated the problem into two stages: designing or learning visual features,…
Multi-Objective Deep Reinforcement Learning
Hossam Mossalam, Yannis M. Assael, Diederik M. Roijers +1
We propose Deep Optimistic Linear Support Learning (DOL) to solve high-dimensional multi-objective decision problems where the relative importances of the objectives are not known…
Learning to Communicate with Deep Multi-Agent Reinforcement Learning
Jakob N. Foerster, Yannis M. Assael, Nando de Freitas +1
We consider the problem of multiple agents sensing and acting in environments with the goal of maximising their shared utility. In these environments, agents must learn communicati…
Alternating Optimisation and Quadrature for Robust Control
Supratik Paul, Konstantinos Chatzilygeroudis, Kamil Ciosek +3
Bayesian optimisation has been successfully applied to a variety of reinforcement learning problems. However, the traditional approach for learning optimal policies in simulators d…
Learning to Communicate to Solve Riddles with Deep Distributed Recurrent Q-Networks
Jakob N. Foerster, Yannis M. Assael, Nando de Freitas +1
We propose deep distributed recurrent Q-networks (DDRQN), which enable teams of agents to learn to solve communication-based coordination tasks. In these tasks, the agents are not…
Probably Approximately Correct Greedy Maximization with Efficient Bounds on Information Gain for Sensor Selection
Yash Satsangi, Shimon Whiteson, Frans A. Oliehoek
Submodular function maximization finds application in a variety of real-world decision-making problems. However, most existing methods, based on greedy maximization, assume it is c…