Declarative-procedural memory interaction in learning agents

• Main Authors: WANG, Wenwen, TAN, Ah-hwee, TEOW, Loo-Nin, TAN Yuan-Sin
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2014
• Subjects: Declarative memory; Memory interaction; Semantic memory; Artificial Intelligence and Robotics; Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/6271; https://ink.library.smu.edu.sg/context/sis_research/article/7274/viewcontent/Declarative_Procedural_Memory_Interaction_in_Learning_Agents___AAMAS_2014.pdf
• Institution: Singapore Management University

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.