本文選題：創(chuàng)意設(shè)計(jì) + 眾包��； 參考：《浙江大學(xué)》2017年博士論文

【摘要】：以互聯(lián)網(wǎng)為基礎(chǔ)的信息物理世界已經(jīng)極大的改變了我們所處的環(huán)境�；ヂ�(lián)網(wǎng)用戶不斷增長(zhǎng)、數(shù)據(jù)不斷涌現(xiàn),推動(dòng)了新一代人工智能的出現(xiàn)。其中,運(yùn)用人工智能解決創(chuàng)造性問(wèn)題,是新一代人工智能研究的重要趨勢(shì)和挑戰(zhàn)。眾包招募大眾參與者完成機(jī)器難以完成的任務(wù),采用眾包解決創(chuàng)造性問(wèn)題,有望結(jié)合人的創(chuàng)意能力與機(jī)器的計(jì)算能力,提升人工智能的創(chuàng)新能力。IBM集團(tuán)、寶馬等企業(yè),美國(guó)疾病預(yù)防與控制中心等政府機(jī)構(gòu)已成功利用眾包收集創(chuàng)意方案;科研人員采用眾包方法招募參與者,輔助研究蛋白質(zhì)結(jié)構(gòu)、尋找物理粒子等。但利用眾包解決創(chuàng)造性問(wèn)題仍存在較大的不確定性�，F(xiàn)有眾包方法多遵循“發(fā)布任務(wù)-回收方案”的模式,以方案質(zhì)量為標(biāo)準(zhǔn)篩選創(chuàng)意方案。此類方法關(guān)注參與者產(chǎn)出方案的質(zhì)量,忽視方案多樣性、方案發(fā)展?jié)摿Φ纫蛩?容易過(guò)早地固化于少數(shù)方案,使得眾包創(chuàng)新能力受限、難以穩(wěn)定產(chǎn)出創(chuàng)新方案。本文以創(chuàng)意設(shè)計(jì)眾包作為研究對(duì)象,提出創(chuàng)意設(shè)計(jì)柔性眾包方法,提升群體智能的創(chuàng)新能力。柔性眾包方法激發(fā)參與者的創(chuàng)新潛力,引導(dǎo)參與者產(chǎn)出多樣化方案;挖掘眾包過(guò)程中的潛力創(chuàng)新方向,篩選有發(fā)展?jié)摿Φ姆桨高M(jìn)行改進(jìn),推動(dòng)方案質(zhì)量的持續(xù)提升。具體的,本文實(shí)施了以下三部分研究:(1)提出創(chuàng)意拐點(diǎn)模型,描述創(chuàng)意設(shè)計(jì)過(guò)程。以創(chuàng)意拐點(diǎn)模型描述創(chuàng)意設(shè)計(jì)眾包,整合參與者在眾包任務(wù)中的創(chuàng)意設(shè)計(jì)過(guò)程,支持對(duì)創(chuàng)意方案發(fā)展過(guò)程的分析。(2)改進(jìn)眾包任務(wù)流程,引導(dǎo)參與者產(chǎn)出多樣化、高質(zhì)量方案。分析參與者的創(chuàng)意設(shè)計(jì)特征,從方案來(lái)源與方案改進(jìn)兩方面優(yōu)化眾包方案生成任務(wù)的流程,促進(jìn)參與者間的創(chuàng)意激發(fā),提升方案質(zhì)量。(3)優(yōu)化眾包過(guò)程中的方案篩選標(biāo)準(zhǔn),關(guān)注創(chuàng)意方案的后續(xù)發(fā)展情況而非當(dāng)前質(zhì)量,挖掘眾包的潛力發(fā)展方向。探索眾包過(guò)程中方案分布、方案間關(guān)系等因素與方案發(fā)展的聯(lián)系,提出創(chuàng)意方案發(fā)展?jié)摿Φ挠?jì)算方法,預(yù)測(cè)方案的后續(xù)發(fā)展情況;以發(fā)展?jié)摿ψ鳛楹Y選標(biāo)準(zhǔn)選擇方案、改進(jìn)方案,持續(xù)提升創(chuàng)意方案的質(zhì)量�；谏鲜龇椒�,本文構(gòu)建了創(chuàng)意設(shè)計(jì)柔性眾包系統(tǒng),在產(chǎn)品設(shè)計(jì)、人機(jī)交互設(shè)計(jì)、平面設(shè)計(jì)三個(gè)創(chuàng)意設(shè)計(jì)領(lǐng)域進(jìn)行了應(yīng)用。實(shí)例證實(shí)創(chuàng)意設(shè)計(jì)柔性眾包方法能夠持續(xù)探索新的設(shè)計(jì)可能性、提升方案原創(chuàng)性,最終產(chǎn)出創(chuàng)新方案。本文分析創(chuàng)意方案的發(fā)展過(guò)程,明確方案發(fā)展的影響因素,據(jù)此評(píng)估方案的發(fā)展?jié)摿?柔性響應(yīng)有潛力的設(shè)計(jì)方向,有望提升群體智能的創(chuàng)新能力,也可為其他眾包方法與創(chuàng)新方法提供啟發(fā)與參考。
[Abstract]:The internet-based world of information physics has dramatically changed our environment. Internet users continue to grow, data continue to emerge, promoting the emergence of a new generation of artificial intelligence. Among them, using artificial intelligence to solve creative problems is an important trend and challenge in the new generation of artificial intelligence research. Crowdsourcing to recruit public participants to complete tasks that are difficult for machines to complete, to solve creative problems by crowdsourcing, hopefully combining human creativity with machine computing, to enhance the innovative capabilities of artificial intelligence. IBM Group, BMW and other enterprises, Government agencies such as the Centers for Disease Control and Prevention have successfully used crowdsourcing to collect creative programs; researchers have used crowdsourcing methods to recruit participants to assist in the study of protein structures and in the search for physical particles. But using crowdsourcing to solve creative problems is still uncertain. Most of the existing crowdsourcing methods follow the mode of "release Task-Recycling Scheme". This kind of method pays attention to the quality of the participant's output scheme, neglects the project diversity, the development potential and so on, and it tends to solidify in a few schemes prematurely, so that the crowdsourcing innovation ability is limited, and it is difficult to stabilize the output innovation scheme. In this paper, creative design crowdsourcing is taken as the research object, and the flexible crowdsourcing method of creative design is proposed to improve the innovation ability of swarm intelligence. Flexible crowdsourcing method can stimulate the innovation potential of participants, guide participants to produce diversified schemes, tap the potential innovation direction in crowdsourcing process, and select potential solutions for improvement, and promote the continuous improvement of project quality. Specifically, this paper implements the following three parts of research: (1) the creative inflection point model is proposed to describe the creative design process. The creative design crowdsourcing model is used to describe the creative design crowdsourcing, to integrate the creative design process of the participants in the crowdsourcing task, and to support the analysis of the creative project development process. (2) to improve the crowdsourcing task process and guide the participants to diversify their output and achieve high quality solutions. This paper analyzes the creative design characteristics of participants, optimizes the process of generating crowdsourcing projects from two aspects of project source and scheme improvement, promotes creative stimulation among participants, and improves the quality of schemes. (3) optimize the selection criteria in crowdsourcing process. Focus on the future development of creative solutions rather than current quality, and tap the potential of crowdsourcing. To explore the relationship between the project distribution and the relationship between the scheme and the development of the project, to put forward the calculation method of the development potential of the creative scheme, to predict the future development of the scheme, and to use the development potential as the selection criteria. Improve programs and improve the quality of creative solutions. Based on the above methods, this paper constructs a flexible crowdsourcing system for creative design, which is applied in three creative design fields: product design, human-computer interaction design and graphic design. Examples show that the flexible crowdsourcing method of creative design can continuously explore new design possibilities, enhance the originality of the scheme, and finally produce innovative solutions. In this paper, the development process of creative scheme is analyzed, and the influencing factors of plan development are defined, according to which the development potential of the scheme is evaluated, and the design direction of flexible response has potential, which is expected to enhance the innovation ability of swarm intelligence. It can also provide inspiration and reference for other crowdsourcing methods and innovative methods.
【學(xué)位授予單位】：浙江大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP18;TB47

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