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arXiv · 1811.10097

Planning in Dynamic Environments with Conditional Autoregressive Models

Johanna Hansen·Kyle Kastner·Aaron Courville·Gregory Dudek
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Abstract

We demonstrate the use of conditional autoregressive generative models (van den Oord et al., 2016a) over a discrete latent space (van den Oord et al., 2017b) for forward planning with MCTS. In order to test this method, we introduce a new environment featuring varying difficulty levels, along with moving goals and obstacles. The combination of high-quality frame generation and classical planning approaches nearly matches true environment performance for our task, demonstrating the usefulness of this method for model-based planning in dynamic environments.

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Johanna Hansen, Kyle Kastner, Aaron Courville, Gregory Dudek. 2018-11-25. Planning in Dynamic Environments with Conditional Autoregressive Models. https://arxiv.org/abs/1811.10097

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