CompCog: Helping people make more future-minded decisions using optimal gamification

CompCog：利用最佳游戏化帮助人们做出更具前瞻性的决策

• 批准号: 1757269
• 负责人: Thomas Griffiths
• 金额: $ 51.94万
• 依托单位: University of California-Berkeley
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-15 至 2019-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1757269&HistoricalAwards=false
• 关键词: CompCog; Helping; people; make; more

Helping people, teams, and organizations achieve important goals may be one of the most effective ways to increase productivity and promote human progress. To achieve their goals, many organizations employ financial incentives or game elements, such as points, levels, and badges, to motivate employees to become more productive. This project develops a theoretical foundation and computational tools for designing better incentive structures to help people achieve their goals. The project connects the crucial challenges of goal achievement studied in psychology to the computational methods from artificial intelligence that can be used to solve them. By bridging this gap the project provides a new way for artificial intelligence to communicate with people and empowers them to overcome the motivational obstacles and cognitive limitations that might otherwise prevent them from making good decisions. At the heart of this project is a mathematical theory for optimizing incentive structures to help people make better decisions in complex, partially unknown environments. This theory is used as the basis for two cognitive prostheses that leverage artificial intelligence and gamification to help people achieve their goals: an intelligent to-do list gamification system that helps people become more productive and procrastinate less and an app that reinforces good habits. Field experiments are used to evaluate whether these cognitive prostheses are effective in the real world, working towards the development of intelligent systems that can aid people in setting and achieving their goals.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

帮助个人、团队和组织实现重要目标，可能是提高生产力、促进人类进步的最有效方式之一。为了实现他们的目标，许多组织采用财务激励或游戏元素，如积分，级别和徽章，以激励员工提高生产力。该项目为设计更好的激励结构提供了理论基础和计算工具，以帮助人们实现目标。该项目将心理学中研究的目标实现的关键挑战与可用于解决这些挑战的人工智能计算方法联系起来。通过弥合这一差距，该项目为人工智能提供了一种与人沟通的新方式，并使他们能够克服动机障碍和认知局限性，否则这些障碍和局限性可能会阻止他们做出正确的决定。该项目的核心是一种优化激励结构的数学理论，以帮助人们在复杂、部分未知的环境中做出更好的决策。这一理论被用作两种认知假体的基础，它们利用人工智能和游戏化来帮助人们实现目标：一种智能待办事项游戏化系统，可以帮助人们提高工作效率，减少拖延，另一种应用程序可以强化良好的习惯。现场实验用于评估这些认知假体在真实的世界中是否有效，致力于开发能够帮助人们设定和实现目标的智能系统。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Resource‐rational Models of Human Goal Pursuit

人类目标追求的资源理性模型

• DOI: 10.1111/tops.12562
• 发表时间: 2021
• 期刊: Topics in Cognitive Science
• 影响因子: 3
• 作者: Prystawski, Ben;Mohnert, Florian;Tošić, Mateo;Lieder, Falk
• 通讯作者: Lieder, Falk

Toward a normative theory of (self-)management by goal-setting

走向通过目标设定进行（自我）管理的规范理论

• DOI: 10.48550/arxiv.2302.02633
• 发表时间: 2023
• 期刊: ArXiv
• 作者: Nishad Singhi;Florian Mohnert;Ben Prystawski;Falk Lieder
• 通讯作者: Falk Lieder