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Optimizing agent behavior over long time scales by transporting value
- Source :
- Nature Communications, Vol 10, Iss 1, Pp 1-12 (2019)
- Publication Year :
- 2019
- Publisher :
- Nature Portfolio, 2019.
-
Abstract
- People are able to mentally time travel to distant memories and reflect on the consequences of those past events. Here, the authors show how a mechanism that connects learning from delayed rewards with memory retrieval can enable AI agents to discover links between past events to help decide better courses of action in the future.
- Subjects :
- Science
Subjects
Details
- Language :
- English
- ISSN :
- 20411723
- Volume :
- 10
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- Nature Communications
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.2e805e7216b343f9a8b03a4f5ce02aad
- Document Type :
- article
- Full Text :
- https://doi.org/10.1038/s41467-019-13073-w