From Reinforcement Learning Towards Artificial General Intelligence

• Type: Article in International Conference Proceedings Book
• Date: 2020

Authors

Filipe Marinho Rocha (Author) Other; Luís Paulo Reis (Author) FEUP

Conference proceedings International

Title: WorldCIST (2)

Pages: 401-413

8th World Conference on Information Systems and Technologies, WorldCIST 2020

7 April 2020 through 10 April 2020

Indexing

Scopus - 4 Citations

INSPEC

Other information

Authenticus ID: P-00S-APS

DOI: 10.1007/978-3-030-45691-7_37

Abstract (EN): The present work surveys research that integrates successfully a number of complementary fields in Artificial Intelligence. Starting from integrations in Reinforcement Learning: Deep Reinforcement Learning and Relational Reinforcement Learning, we then present Neural-Symbolic Learning and Reasoning since it is applied to Deep Reinforcement Learning. Finally, we present integrations in Deep Reinforcement Learning, such as, Relational Deep Reinforcement Learning. We propose that this road is breaking through barriers in Reinforcement Learning and making us closer to Artificial General Intelligence, and we share views about the current challenges to get us further towards this goal. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 13