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NETWORK: People-centred Computational Environments for Design and Decision-making

网络：以人为本的设计和决策计算环境

基本信息

批准号：
EP/E001939/1
负责人：
Ian Parmee
金额：
$ 7.89万
依托单位：
University of the West of England
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2006
资助国家：
英国
起止时间：
2006 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=EP%2FE001939%2F1
关键词：
NETWORK People centred Computational Environments

项目摘要

Current computer-aided design and decision support tools support the later, well defined stages of problem solving where a product or objective is physical, tangible, and comprehensible. However, more abstract concept formulation and development is poorly supported, especially where uncertainty is an inherent characteristic. Furthermore, computer-aided design and decision-support tends to be domain specific. There is little or no exploitation of cross-domain experience. The Network proposes to investigate, develop and implement research and development agendas that have the potential to redress both these imbalances. During the early stages of any design or decision-making activity people play a major common role. Differing aspects need to be concurrently considered. For instance those relating to multiple options, constraints and objectives; human-based knowledge and experience; the environment for which we are designing and the people affected by our designs / decisions. Inherent uncertainty and poor problem definition initially exacerbate the situation. Preliminary computer-based problem representations may comprise fuzzy concepts and sparse information. Further, such representations change as information and knowledge accumulates from initial search and exploration and associated human assimilation. Human experience plays a major role. People-centred systems are therefore required that meld such knowledge with computer-based simulation, search and exploration, data processing and data visualization. The decision-maker should become immersed in the system involved in an iterative process of data generation; evaluation and analysis; subsequent modification of the computer-based representation and further exploration of the redefined space. The utility of relatively established computational intelligence technologies will be reassessed in the light of their current usage. Network investigations will extend into current associated areas of research and the potential of new, emerging technologies. These will not be considered stand-alone but will be investigated alongside a range of well-established enabling computational technologies to ensure successful integration. The complexity of the domain is such that much further collaborative working is required to identify such primary research and development areas that will result in generic, people-centred computational systems for early design and decision-making processes. Very significant cross-disciplinary interest is evident. The potential of people-centred computation across varied decision-making processes is now being identified. Business/organizational structure, financial systems and resource allocation/scheduling are just a small example of areas that can benefit from the envisaged systems. It is our intention to develop the Network membership to ensure that such areas are well-covered and are in a position to benefit from collective reasoning, collaborative research, workshops and training events. It is also essential that members representing the large body of research relating to statistical, intelligent systems and more deterministic approaches to dealing with uncertainty and risk in decision processes are included. Much mutual benefit could arise from a melding of established techniques and strategies and emerging people-centred systems. The strength of the Network will lie in the collaboration of seemingly disparate cognitive disciplines that require a common core expertise to support decision-making processes. The result will be the identification of mutually symbiotic design and decision-making environments which create new potential interfaces for capturing and enabling discovery and innovation.

当前的计算机辅助设计和决策支持工具支持解决问题的后期定义明确的阶段，其中产品或目标是物理的，有形的和可理解的。然而，更抽象的概念制定和发展的支持不足，特别是在不确定性是一个固有的特点。此外，计算机辅助设计和决策支持往往是特定领域的。很少或根本没有利用跨领域的经验。该网络提议调查、制定和执行有可能纠正这两种不平衡的研究和发展议程。在任何设计或决策活动的早期阶段，人们都发挥着重要的共同作用。不同的方面需要同时考虑。例如，与多个选项、约束和目标有关的问题;以人为本的知识和经验;我们设计的环境以及受我们设计/决策影响的人。固有的不确定性和对问题的不明确定义最初使情况恶化。初步的基于计算机的问题表示可以包括模糊概念和稀疏信息。此外，随着信息和知识从最初的搜索和探索以及相关的人类同化中积累，这种表征也会发生变化。人类经验起着重要作用。因此，需要建立以人为本的系统，将这些知识与基于计算机的模拟、搜索和探索、数据处理和数据可视化相结合。决策者应该沉浸在系统中，参与数据生成的迭代过程;评估和分析;随后修改基于计算机的表示和进一步探索重新定义的空间。相对成熟的计算智能技术的效用将根据其目前的使用情况重新评估。网络调查将扩展到当前相关的研究领域和新兴技术的潜力。这些将不会被认为是独立的，但将与一系列成熟的使能计算技术一起进行研究，以确保成功的整合。该领域的复杂性是如此之大，需要进一步的合作工作，以确定这些主要的研究和开发领域，这将导致通用的，以人为本的计算系统的早期设计和决策过程。非常重要的跨学科的兴趣是显而易见的。目前正在确定以人为本的计算在各种决策过程中的潜力。业务/组织结构、财务制度和资源分配/时间安排只是可从设想的系统中受益的领域的一个小例子。我们打算发展该网络的成员，以确保这些领域得到充分的覆盖，并能够从集体推理、合作研究、讲习班和培训活动中受益。同样重要的是，代表与统计、智能系统和处理决策过程中的不确定性和风险的更确定性方法有关的大量研究的成员也必须包括在内。将既定的技术和战略与新出现的以人为本的制度相结合，可以产生许多互利。该网络的优势在于看似不同的认知学科的合作，这些学科需要共同的核心专业知识来支持决策过程。其结果将是确定相互共生的设计和决策环境，创造新的潜在接口，捕捉和实现发现和创新。