NettetLearning Compositional Neural Programs with Recursive Tree Search and Planning. Thomas Pierrot *, Guillaume Ligner *, Scott Reed, Olivier Sigaud *, Nicolas Perrin *, Alexandre Laterre *, David Kas *, Karim Beguir *, Nando de … NettetLearning transferable graph exploration. Pages 2518–2529. Previous Chapter Next Chapter. ABSTRACT. This paper considers the problem of efficient exploration of …
Learning Graph Structure With A Finite-State Automaton Layer
Nettet6. des. 2024 · Learning transferable graph exploration. In Advances in Neural Information Processing Systems, pages 2518-2529. Learning to act by predicting the future. Jan 2016; A Dosovitskiy; V Koltun; NettetPDF - This paper considers the problem of efficient exploration of unseen environments, a key challenge in AI. We propose a `learning to explore' framework where we learn a policy from a distribution of environments. At test time, presented with an unseen environment from the same distribution, the policy aims to generalize the exploration … food network celebrities
PDF - Learning Transferable Graph Exploration
NettetWe formulate this task as a reinforcement learning problem where the exploration' agent is rewarded for transitioning to previously unseen environment states and employ a … Nettet28. okt. 2024 · This paper considers the problem of efficient exploration of unseen environments, a key challenge in AI. We propose a `learning to explore' framework where we learn a policy from a distribution of environments. At test time, presented with an unseen environment from the same distribution, the policy aims to generalize the … NettetLearning Transferable Graph Exploration: The paper is concerned with learning a general exploration policy, trained using reinforcement learning and considering a distribution of graph-structured environments. A motivating application is coverage-guided program testing (fuzzing). food network cauliflower recipes