{"type":"ScholarlyArticle","title":"Direct Code Access in Self-Organizing Neural Networks for Reinforcement Learning","authors":[{"name":"Ah-Hwee Tan","slug":"ah-hwee-tan","given":"Ah-Hwee","family":"Tan","affiliation":""}],"abstract":"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.","doi":null,"url":"https://ijcai.org/proceedings/2007/173","pdf":"https://ijcai.org/proceedings/2007/0173.pdf","markdown":"https://ijcai.org/proceedings/2007/173.md","bibtex":"https://ijcai.org/proceedings/2007/bibtex/173","volume":{"slug":"2007","title":"Proceedings of the Twentieth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2007","url":"https://ijcai.org/proceedings/2007/","year":2007,"location":"Hyderabad, India","dates":"","editors":"Ramon López de Mántaras","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":173,"pages":{"first":1071,"last":1075},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}