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Showing 1 to 3 of 3 for “"Policy Optimisation"”.

  1. Reinforcement Learning and Reward Estimation for Dialogue Policy Optimisation

    … space, reinforcement learning-based dialogue policy optimisation is often slow. This thesis presents several approaches to address these problems. To better evaluate a dialogue for policy optimisation, two methods are proposed. First, a recurrent neural network-based predictor pre-trained from …

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  2. Data-Driven Policy Optimisation for Multi-Domain Task-Oriented Dialogue

    … an efficient way of learning a dialogue policy in new domains. Secondly, it is important to have the ability to collect and utilise human-human conversational data to bootstrap an agent's knowledge. The work presented in this thesis demonstrates how a neural dialogue manager fine-tuned …

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  3. Sample-Efficient Reinforcement Learning for Spoken Dialogue Systems

    … the outputs of both critics to optimize the policy. Through experiments, we demonstrate the robustness of ADC in noisy environments where accurate modeling of user behavior is challenging. Furthermore, ADC exhibits superior sample efficiency and stability compared to its model-free baseline. …

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