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A Review of Symbolic, Subsymbolic and Hybrid Methods for Sequential Decision Making by Núñez-Molina, Carlos; Mesejo, Pablo; Fernández-Olivares, Juan is a scholarly article available to read on EtoBox.

What is A Review of Symbolic, Subsymbolic and Hybrid Methods for Sequential Decision Making about?

In the field of Sequential Decision Making (SDM), two paradigms have historically vied for supremacy: Automated Planning (AP) and Reinforcement Learning (RL). In the spirit of reconciliation, this article reviews AP, RL and hybrid methods (e.g., novel learn to plan techniques) for solving Sequential Decision Processes (SDPs), focusing on their knowledge representation: symbolic, subsymbolic, or a combination. Additionally, it also covers methods for learning the SDP structure. Finally, we compare the advantages and drawbacks of the existing methods and conclude that neurosymbolic AI poses a promising approach for SDM, since it combines AP and RL with a hybrid knowledge representation.

Author

Núñez-Molina, Carlos; Mesejo, Pablo; Fernández-Olivares, Juan

Published

2023

Language

EN