Object-oriented state editing for HRL

Autor:	Bapst, Victor, Sanchez-Gonzalez, Alvaro, Shams, Omar, Stachenfeld, Kimberly, Battaglia, Peter W., Singh, Satinder, Hamrick, Jessica B.
Rok vydání:	2019
Předmět:	Computer Science - Machine Learning Computer Science - Artificial Intelligence Statistics - Machine Learning
Druh dokumentu:	Working Paper
Popis:	We introduce agents that use object-oriented reasoning to consider alternate states of the world in order to more quickly find solutions to problems. Specifically, a hierarchical controller directs a low-level agent to behave as if objects in the scene were added, deleted, or modified. The actions taken by the controller are defined over a graph-based representation of the scene, with actions corresponding to adding, deleting, or editing the nodes of a graph. We present preliminary results on three environments, demonstrating that our approach can achieve similar levels of reward as non-hierarchical agents, but with better data efficiency. Comment: 8 pages; accepted to the Perception as Generative Reasoning workshop of the 33rd Conference on Neural InformationProcessing Systems (NeurIPS 2019)
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1910.14361 Zobrazit plný text záznamu View this record from Arxiv