Developing Human-Like Game Agents with a Wide Range of Play Styles and Skill Levels
Lead Research Organisation:
Queen Mary University of London
Department Name: Sch of Electronic Eng & Computer Science
Abstract
AI agents that perform with superhuman skill in increasingly complex games have appeared in recent years, but these agents are not always useful to game developers. AI agents can aid in the game development process by representing the skill levels and play styles of players. The proposed research will focus on three areas: measuring skill and play styles, developing game agents that mimic a range of human play styles and skill levels, and making these agents human-like. Upon successful completion, this research has potential to improve the development process via automated playtesting and to introduce AI agents that are more engaging and interactive.
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
EP/S022325/1 | 01/10/2019 | 31/03/2028 | |||
2890040 | Studentship | EP/S022325/1 | 01/10/2023 | 30/09/2027 | Ruizhe Yu Xia |