Adaptation of an adversarial non-player character through case based reasoning

Authors

Danny C. Cheng, De La Salle University, Manila
Gian Kristian A. Fontanilla, De La Salle University, Manila
Anne Marie M. Africa, De La Salle University, Manila
Karmela Angela G. Cortez, De La Salle University, Manila
Paul Michael O. Go, De La Salle University, Manila

College

College of Computer Studies

Department/Unit

Software Technology

Document Type

Archival Material/Manuscript

Abstract

Game development is now turning to other innovations such as applying Artificial Intelligence (AI) techniques [4]. However, such algorithms only make use of simple decision making and still lack the ability to learn [2] One type of game that requires this kind of learning is real time strategy games. This research intends to present the CAN system that is designed as an adversarial Non Player Characters (NPC) that learns strategies in a real time strategy (RTS) game using Case-based Reasoning. Using strategies learned from the past actions of the human player. CAN is able to adapt to current situation and change strategy online.

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Recommended Citation

Cheng, D. C., Fontanilla, G. A., Africa, A. M., Cortez, K. G., & Go, P. O. (2022). Adaptation of an adversarial non-player character through case based reasoning. Retrieved from https://animorepository.dlsu.edu.ph/faculty_research/5165

Disciplines

Artificial Intelligence and Robotics

Keywords

Artificial intelligence; Games of strategy (Mathematics); Game theory—Computer programs

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