Direct Code Access in Self-Organizing Neural Networks for Reinforcement Learning

TD-FALCON is a self-organizing neural network that incorporates Temporal Difference (TD) methods for reinforcement learning. Despite the advantages of fast and stable learning, TD-FALCON still relies on an iterative process to evaluate each available action in a decision cycle. To remove this deficiency, this paper presents a direct code access procedure whereby TD-FALCON conducts instantaneous searches for cognitive nodes that match with the current states and at the same time provide maximal reward values. Our comparative experiments show that TD-FALCON with direct code access produces comparable performance with the original TD-FALCON while improving significantly in computation efficiency and network complexity.

• Type: Conference
• Year: 2007
• Where: IJCAI
• Authors: Ah-Hwee Tan
• Keywords: Artificial Intelligence, Code Access Procedure, Direct Code Access, IJCAI 2007, Self-organizing Neural Network