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Deep neural network representations play an important role in computer vision, speech, computational linguistics, robotics, reinforcement learning and many other data-rich domains. In this talk I… (More)
- Harm van Seijen, Hado van Hasselt, Shimon Whiteson, Marco Wiering
- 2009 IEEE Symposium on Adaptive Dynamic…
- 2009
This paper presents a theoretical and empirical analysis of Expected Sarsa, a variation on Sarsa, the classic on-policy temporal-difference method for model-free reinforcement learning. Expected… (More)
- Shimon Whiteson, Peter Stone
- Journal of Machine Learning Research
- 2006
Temporal difference methods are theoretically grounded and empirically effective methods for addressing sequential decision making problems with delayed rewards. Most problems of real-world interest… (More)
Feature selection is the process of finding the set of inputs to a machine learning algorithm that will yield the best performance. Developing a way to solve this problem automatically would make… (More)
- Matthew E. Taylor, Shimon Whiteson, Peter Stone
- AAMAS
- 2007
The ambitious goal of transfer learning is to accelerate learning on a target task after training on a different, but related, source task. While many past transfer methods have focused on… (More)
Many real-world problems, such as network packet routing and the coordination of autonomous vehicles, are naturally modelled as cooperative multi-agent systems. There is a great need for new… (More)
- Diederik M. Roijers, Peter Vamplew, Shimon Whiteson, Richard Dazeley
- J. Artif. Intell. Res.
- 2013
Sequential decision-making problems with multiple objectives arise naturally in practice and pose unique challenges for research in decision-theoretic planning and learning, which has largely focused… (More)
- Masrour Zoghi, Shimon Whiteson, Rémi Munos, Maarten de Rijke
- ICML
- 2014
This paper proposes a new method for the K-armed dueling bandit problem, a variation on the regular K-armed bandit problem that offers only relative feedback about pairs of arms. Our approach extends… (More)
Decentralized partially observable Markov decision processes (Dec-POMDPs) constitute an expressive framework for multiagent planning under uncertainty, but solving them is provably intractable. We… (More)
Evaluation methods for information retrieval systems come in three types: offline evaluation, using static data sets annotated for relevance by human judges; user studies, usually conducted in a… (More)