JAIST Repository
https://dspace.jaist.ac.jp/Title

ゲームエンターテイメントと報酬の計算手法の評価

Author(s)高, 娜穎Citation
Issue Date

2024-03

TypeThesis or Dissertation

Text version

ETDURLhttp://hdl.handle.net/10119/19064

RightsDescription

Supervisor: 飯田 弘之, 先端科学技術研究科, 博士

Japan Advanced Institute of Science and Technology

Abstract
The Game Refinement (GR) theory, widely employed for assessing the enjoyment andintricacy of games, is herein examined through the lens of audience perception. This
theory delves into the cognitive information processes occurring in our minds while engaging in strategy games, in adherence to the principles set forth by Newton’s laws. Its
central focus is on the uncertainty surrounding game outcomes, employing abstraction
to dissect game components and assess the progression of game information based onachievements and game duration.
The quantification of this progression leads to the measurement of informational
acceleration, akin to Newton’s second law (F = ma), wherein informational acceleration correlates with mental force and excitement. Changes in acceleration significantly
impact game dynamics, especially in high-stress scenarios, and can be rectified using“jerk” values derived from acceleration readings. In this context, a comprehensive exploration of various physical factors influencing psychological experiences in gaming isconducted.
This study prominently emphasizes the intersection of physical and psychologicalelements by depicting the progression of game information within our minds. By establishing reasonable informational jerk values associated with the success rate andinformational acceleration of the game process, the development of game refinement
theory enhances the overall player experience.
The concept of “jerk”, signifying a sudden change in acceleration, is a fascinatingphenomenon experienced by humans and possesses practical applications in mechanicaliand engineering domains, such as elevator rides. The paper forges a connection between
the logistical model of game progression and “jerk” measurements, particularly in gameswith incomplete information, typified as AD values (representing addiction and thepropensity for repeated gameplay).
To investigate the implications of AD values concerning GR metrics and its extension, the motion in mind model, several popular card games, including Wakeng,Doudizhu, Winner, Big Two, and Tien Len, are utilized. Self-playing simulations conducted by artificial intelligence (AI) agents validate these findings with empirical data,
yielding valuable insights into game design and gameplay experiences.
Players of varying skill levels may encounter and endure diverse reward frequencies denoted as N and jerk values during the progression of game information. Thus,
an exploration into the interplay between the player’s performance level (k), reward
frequency (N ), and jerk values is undertaken.
The inherent game risk, often represented as “m” is a well-acknowledged factor.
To overcome these challenges, players must skillfully devise strategies. Exceptionallyskilled players can navigate uncertainties with ease, characterized by a game velocity
represented as v⃗0 = 1 − m.
However, players possess differing abilities, resulting in varying levels of proficiency
in dealing with uncertainties. Prior research employs “k” as a measure of performance,
where higher values indicate lower performance. For imperfect players, the game velocity can be calculated as v⃗k = (1 − km)v⃗0 = (1 − km)(1 − m).
In the realm of reinforcement learning, “N ” often signifies the “number of steps”
or “time steps”, representing the interval for acquiring rewards. In games with perfectinformation, players possess complete knowledge of moves, while imperfect information
games entail partial insights or educated guesses. In such instances, “N ” can symbolize
the number of actions considered during decision-making, akin to the Monte Carlo Tree
Search algorithm.
In this study, the Game Refinement (GR) theory is explored from the perspectiveii

of the audience. The theory focuses on the cognitive processes that occur while playing strategy games, emphasizing the uncertainty of game outcomes and how it affects
player experience. It introduces the concept of “jerk” to measure sudden changes inacceleration in games. The study investigates the relationship between “AD” values,
representing addiction and repeat gameplay, and GR metrics in various card games.
Additionally, it delves into the interplay of player performance (k), reward frequency(N ), and unpredictability (AD) in gaming. This research provides valuable insights
into game design and gameplay experiences.
Keyword: Game refinement theory;Motion in mind ;Perfect information game;Imperfectinformation game;Card game;Jerk ;Addiction;iii