Hierarchical Pathfinding and AI-Based Learning Approach in Strategy Game Design. (24th March 2008)

• Record Type: Journal Article
• Authors: Duc, Le Minh; Sidhu, Amandeep Singh; Chaudhari, Narendra S.
• Other Names: Wong Kok Wai Academic Editor.
• Is Part Of: International journal of computer games technology. Volume 2008(2008)
• Publication Date: 2008-03-24
• Subjects: Computer games -- Design -- Periodicals; Computer games -- Programming -- Periodicals; Jeux d'ordinateur; Jeux d'ordinateur -- Programmation; Computer games -- Design; Computer games -- Programming; Electronic journals; Periodicals; 794.81
• DOI: 10.1155/2008/873913
• Languages: English
• ISSNs: 1687-7047

Abstract

Abstract : Strategy game and simulation application are an exciting area with many opportunities for study and research. Currently most of the existing games and simulations apply hard coded rules so the intelligence of the computer generated forces is limited. After some time, player gets used to the simulation making it less attractive and challenging. It is also costly and tedious to incorporate new rules for an existing game. The main motivation behind this research project is to improve the quality of artificial intelligence- (AI-) based on various techniques such as qualitative spatial reasoning (Forbus et al., 2002), near-optimal hierarchical pathfinding (HPA * ) (Botea et al., 2004), and reinforcement learning (RL) (Sutton and Barto, 1998).