Computational Problems & Cognitive Functions: Modeling, Characterizations, and Solutions

计算问题

• 批准号: RGPIN-2016-05505
• 负责人: Stege, Ulrike
• 金额: $ 1.6万
• 依托单位: University of Victoria
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=678631
• 关键词: Computational; Problems; Cognitive; Functions; Modeling

Due to rapidly advancing technology, many internet of things devices and apps now extend human capabilities, ranging from support for experts to everyday activities. As highlighted in IBM's News Room, David Stokes, Chief Executive for IBM, UK and Ireland, posits that "We're at the dawn of a new era of cognitive computing, during which advanced data-centric computing models and open innovation approaches will allow technology to greatly augment decision-making capabilities for business and government." Research on this topic is commonly referred to as human problem solving (HPS).***To advance research in this field, an increased understanding of the how, when and what of HPS is required. Fundamental to this endeavour is the characterization of cognitive functions. My research program investigates fundamental questions: What problems can people solve successfully? Which ones cannot be solved? What are the properties of the ones that people are interested in solving? What are successful solving strategies? We might find answers to some of these questions in the properties of games and puzzles, such as Sudoku.***To identify and characterize cognitive functions, we draw on methods in classical and parameterized complexity, the development of exact algorithms, as well as empirical studies and their analyses. As an effective data collection and problem solving platform for our empirical studies, we intend to utilize Lively, an open source infrastructure for Web applications programming.***An improved understanding of human problem solving impacts many different application areas directly, including but not limited to: ***(a) The game-design industry. Methods for identifying properties of the cognitive functions used when playing games or puzzles that many people are attracted to and intrigued by while having a satisfactory playing experience will provide the industry with strategies and tools to create new games involving these properties.***(b) The design of software in general and the quality of self-adaptive systems in particular. For example to design self-driving cars that are safer than human operated cars, it is beneficial to understand how humans make decisions on the road. This will aid the design software functions that have to react to human decision making in other cars. ***(c) Education. The knowledge gained will be informative for educators at all levels, including teaching problem solving skills.***(d) Training. Highly qualified personnel (HQP) trained in this area and in my research group in particular acquire an interdisciplinary education based on solid foundations in theoretical computer science, and learn how to conduct empirical studies. These HQP are highly sought after by industry in general, and in Canada in particular. *** *** **

由于技术的快速进步，许多物联网设备和应用程序现在扩展了人类的能力，从支持专家到日常活动。正如IBM的新闻编辑室所强调的那样，IBM英国和爱尔兰首席执行官David Stokes认为，“我们正处于认知计算新时代的黎明，在这个时代，先进的以数据为中心的计算模型和开放的创新方法将使技术能够极大地增强企业和政府的决策能力。”对这一主题的研究通常被称为人类问题解决(HPS)。*为了推进这一领域的研究，需要对HPS的方式、时间和内容有更多的了解。这一努力的根本是确定认知功能的特征。我的研究项目调查的是基本问题：人们可以成功地解决什么问题？哪些是解决不了的？人们有兴趣解决的问题的性质是什么？什么是成功的解决策略？我们可能会在游戏和谜题的性质中找到其中一些问题的答案，例如数独。*为了识别和表征认知功能，我们借鉴了经典和参数复杂性、精确算法的发展以及实证研究和分析的方法。作为我们的实证研究的有效数据收集和问题解决平台，我们打算利用用于Web应用程序编程的开源基础设施Liful。*对人类问题解决的更好的理解直接影响到许多不同的应用领域，包括但不限于：*(A)游戏设计行业。在具有满意的游戏体验的同时，识别在玩游戏或谜题时所使用的认知功能的属性的方法将为该行业提供策略和工具，以创建涉及这些属性的新游戏。*(B)总体上的软件设计，特别是自适应系统的质量。例如，要设计比人类驾驶的汽车更安全的自动驾驶汽车，了解人类如何在道路上做出决定是有益的。这将有助于设计软件功能，这些功能必须对其他汽车中的人类决策做出反应。*(C)教育。获得的知识将为各级教育工作者提供信息，包括教授解决问题的技能。*(D)培训。在这一领域，特别是在我的研究小组中接受培训的高素质人员(HQP)获得了基于扎实的理论计算机科学基础的跨学科教育，并学习如何进行实证研究。这些HQP普遍受到工业界的追捧，特别是在加拿大。*