NettetThe main components of our method are: learning reachability estimates (via Q-learning and regression), learning a latent space (via an auto-encoder with reachability … NettetPlanning - the ability to analyze the structure of a problem in the large and decompose it into interrelated subproblems - is a hallmark of human intelligence. While deep reinforcement learning (RL) has shown great promise for solving relatively straightforward control tasks, it remains an open problem how to best incorporate planning into …

World Model as a Graph: Learning Latent Landmarks for Planning

NettetIn this work, we propose to learn graph-structured world models composed of sparse, multi-step transitions. We devise a novel algorithm to learn latent landmarks that are … NettetarXiv.org e-Print archive nursery baskets with liners

Proceedings of Machine Learning Research

NettetAbstract. Spectral methods for manifold learning and clustering typically construct a graph weighted with affinities from a dataset and compute eigenvectors of a graph Laplacian. With large datasets, the eigendecomposition is too expensive, and is usually approximated by solving for a smaller graph defined on a subset of the points … Nettet25. nov. 2024 · We devise a novel algorithm to learn latent landmarks that are scattered (in terms of reachability) across the goal space as the nodes on the graph. In this same … NettetWe devise a novel algorithm to learn latent landmarks that are scattered (in terms of reachability) across the goal space as the nodes on the graph. ... Learning Latent Landmarks for Planning (ICML 2024 Long Presentation). By Lunjun Zhang, Ge Yang, Bradly Stadie. A link to our paper can be found on arXiv. Videos / blog can be found on … nursery barstow ca