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Clustering from an Optimization viewpoint Exploration and Exploitation using Upper Confidence Bounds

Clustering from an Optimization viewpoint Exploration and Exploitation using Upper Confidence Bounds

This video was recorded at Workshop on Principled Methods of Trading Exploration and Exploitation London, 2005. Traditional off-line learning methods are often not appropriate for applications in user modelling and user interfaces since to be useful the system must learn about the user or context during the process of interaction 'on the fly'. This immediately raises the fundamental problem of trading off exploration and exploitation in that as information is learnt the system may be tempted to act in line with this insight rather than further exploring alternatives. Machine learning has developed a number of models that attempt to capture and analyse this trade-off, from the simplest bandit problem to the full Markov decision processes underlying reinforcement learning. The workshop... Show More

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