Publication Type
Conference Proceeding Article
Version
acceptedVersion
Publication Date
5-2014
Abstract
It has been well recognized that human makes use of both declarative memory and procedural memory for decision making and problem solving. In this paper, we propose a computational model with the overall architecture and individual processes for realizing the interaction between the declarative and procedural memory based on self-organizing neural networks. We formalize two major types of memory interactions and show how each of them can be embedded into autonomous reinforcement learning agents. Our experiments based on the Toad and Frog puzzle and a strategic game known as Starcraft Broodwar have shown that the cooperative interaction between declarative knowledge and procedural skills can lead to significant improvement in task performance.
Keywords
Declarative memory, Memory interaction, Semantic memory
Discipline
Artificial Intelligence and Robotics | Databases and Information Systems
Research Areas
Data Science and Engineering
Publication
Proceedings of the 13th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2014): Paris, May 5-9
Volume
2
First Page
1475
Last Page
1476
ISBN
9781634391313
Publisher
IFAAMAS
City or Country
Richland, SC
Citation
1
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.