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 …
Learning transferable graph exploration
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Nettet11. mar. 2024 · Exploration은 인공지능 분야에 있어서 근본적인 문제였다. exploration과 exploitation의 문제에서처럼 말이다. 이 논문에서는 모르는 미지의 환경 (학습이 이루어지지 않았던 환경)이 주어졌을 때, exploration의 여러가지 문제를 커버하고자 하려고 한다. 그래서 본 … Nettet17. apr. 2024 · We focus on diffusion convolutional recurrent neural network (DCRNN), a state-of-the-art graph neural network for highway network forecasting. It models the complex spatial and temporal dynamics of the highway network using a graph-based diffusion convolution operation within a recurrent neural network. DCRNN cannot …
NettetWe particularly focus on environments with graph-structured state-spaces that are encountered in many important real-world applications like software testing and map … 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).
NettetLearning Transferable Graph Exploration Hanjun Dai"†⇤, Yujia Li§, Chenglong Wang‡, Rishabh Singh†, Po-Sen Huang§, Pushmeet Kohli§ " Georgia Institute of Technology † … NettetLearning Transferable Graph Exploration Hanjun Dai, Yujia Li, Chenglong Wang, Rishabh Singh, Po-Sen Huang, Pushmeet Kohli 33rd Conference on Neural …
Nettet30. mai 2024 · This paper studies the problem of autonomous exploration under localization uncertainty for a mobile robot with 3D range sensing. We present a framework for self-learning a high-performance exploration policy in a single simulation environment, and transferring it to other environments, which may be physical or virtual. Recent work …
NettetWe particularly focus on environments with graph-structured state-spaces that are encountered in many important real-world applications like software testing and map … mpi collective goodsNettetWe particularly focus on environments with graph-structured state-spaces that are encountered in many important real-world applications like software testing and map building. We formulate this task as a reinforcement learning problem where the `exploration' agent is rewarded for transitioning to previously unseen environment … mpich安装失败NettetLearning Transferable Graph Exploration The paper is concerned with learning a general exploration policy, trained using reinforcement learning and considering a … mpich programsNettet28. okt. 2024 · Request PDF Learning Transferable Graph Exploration This paper considers the problem of efficient exploration of unseen environments, a key … mpi coldwater msNettet28. okt. 2024 · We particularly focus on environments with graph-structured state-spaces that are encountered in many important real-world applications like software testing and … mpich testNettet13. mar. 2024 · This open source library is available to summarize several years of research papers on graph reinforcement learning for the convenience of researchers. … mpico malawi contactsNettetYear Venue Model Title Algorithm Paper Code; 2024: NeurIPS: GMETAEXP: Learning Transferable Graph Exploration: MDP: Paper \ 2024: arXiv: Ekar: Ekar: An … mpich-tofu