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

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

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...

Full description

Saved in:
Bibliographic Details
Main Authors: Cheng, Danny C., Fontanilla, Gian Kristian A., Africa, Anne Marie M., Cortez, Karmela Angela G., Go, Paul Michael O.
Format: text
Published: Animo Repository 2022
Subjects:
Artificial intelligence
Games of strategy (Mathematics)
Game theory—Computer programs
Artificial Intelligence and Robotics
Online Access:https://animorepository.dlsu.edu.ph/faculty_research/5165
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: De La Salle University
Description
Summary: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.

Similar Items