Jul 18, 2021 · In this chapter, we describe the continual model-based analysis (CMBA) framework as an approach for analysing a system under continual change.
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Sep 27, 2024 · We propose DRAGO, a novel approach for continual model-based reinforcement learning aimed at improving the incremental development of world models.
Apr 30, 2024 · We present a method that addresses the pain point of long lead-time required to deploy cell-level parameter optimisation policies to new wireless network sites.
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Effective planning in model-based reinforcement learning (MBRL) and model-predictive control (MPC) relies on the accuracy of the learned dynamics model.
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We discuss a recent approach to investigating cognitive control, which has the potential to deal with some of the challenges inherent in this endeavour.
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Dec 2, 2021 · In this chapter, we describe the continual model-based analysis (CMBA) framework as an approach for analysing a system under continual ...
Abstract. Finding an optimal policy in a reinforcement learning (RL) framework with continuous state and action spaces is challenging. Approximate solutions.
Missing: Continual Analysis.
Effective planning in model-based reinforcement learning (MBRL) and model-predictive control (MPC) relies on the accuracy of the learned dynamics model.
Sep 17, 2023 · We present a method that addresses the pain point of long lead-time required to deploy cell-level parameter optimisation policies to new wireless network sites.
Model-based approach attempts to segment and detects every single individual in the crowd scene and then counting them using a model or appearance of human ...