Osawa Hirotaka, Kawagoe Atsushi, Sato Eisuke, Kato Takuya
Human-Agent Interaction Laboratory, Faculty of Engineering, Information and Systems, University of Tsukuba, Tsukuba, Japan.
Human-Agent Interaction Laboratory, Graduate School of Science and Technology, University of Tsukuba, Tsukuba, Japan.
Front Robot AI. 2021 Oct 12;8:658348. doi: 10.3389/frobt.2021.658348. eCollection 2021.
The authors evaluate the extent to which a user's impression of an AI agent can be improved by giving the agent the ability of self-estimation, thinking time, and coordination of risk tendency. The authors modified the algorithm of an AI agent in the cooperative game Hanabi to have all of these traits, and investigated the change in the user's impression by playing with the user. The authors used a self-estimation task to evaluate the effect that the ability to read the intention of a user had on an impression. The authors also show thinking time of an agent influences impression for an agent. The authors also investigated the relationship between the concordance of the risk-taking tendencies of players and agents, the player's impression of agents, and the game experience. The results of the self-estimation task experiment showed that the more accurate the estimation of the agent's self, the more likely it is that the partner will perceive humanity, affinity, intelligence, and communication skills in the agent. The authors also found that an agent that changes the length of thinking time according to the priority of action gives the impression that it is smarter than an agent with a normal thinking time when the player notices the difference in thinking time or an agent that randomly changes the thinking time. The result of the experiment regarding concordance of the risk-taking tendency shows that influence player's impression toward agents. These results suggest that game agent designers can improve the player's disposition toward an agent and the game experience by adjusting the agent's self-estimation level, thinking time, and risk-taking tendency according to the player's personality and inner state during the game.
作者评估了赋予人工智能代理自我评估能力、思考时间和风险倾向协调能力，在多大程度上可以改善用户对该代理的印象。作者修改了合作游戏《璀璨宝石》中人工智能代理的算法，使其具备所有这些特质，并通过与用户一起玩游戏来研究用户印象的变化。作者使用自我评估任务来评估读取用户意图的能力对印象的影响。作者还表明，代理的思考时间会影响对该代理的印象。作者还研究了玩家与代理的冒险倾向一致性、玩家对代理的印象以及游戏体验之间的关系。自我评估任务实验的结果表明，代理对自身的评估越准确，伙伴就越有可能在该代理中感知到人性、亲和力、智慧和沟通技巧。作者还发现，当玩家注意到思考时间的差异时，根据行动优先级改变思考时间长度的代理，会给人比思考时间正常的代理或随机改变思考时间的代理更聪明的印象。关于冒险倾向一致性的实验结果表明，这会影响玩家对代理的印象。这些结果表明，游戏代理设计师可以通过根据玩家在游戏中的个性和内心状态调整代理的自我评估水平、思考时间和冒险倾向，来改善玩家对代理的态度和游戏体验。
