Pilot: Using Causal Relations to Guide Multi-Level Creative Processes
试点:利用因果关系指导多层次的创作过程
基本信息
- 批准号:0753845
- 负责人:
- 金额:$ 20万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2008
- 资助国家:美国
- 起止时间:2008-08-01 至 2011-08-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
While evolutionary computing to support creativity appears very promising, current methods include human creativity to directly guide the search process and to replace the fitness function so the creativity is not part of the computational process. This project considers causal relations and cause and effect reasoning as important aspects of human creativity in problem solving, scientific discovery, invention and design. The primary goal of this research is to develop and evaluate methods for causally guided evolutionary creativity by incorporating cause and effect relationships as part of the fitness function. This project will develop an understanding of the fundamental principles involved in integrating causal inference with the genetic search process that has been used successfully in past creative evolutionary systems. Undergraduate students will be encouraged to integrate their own projects within the proposed creative evolutionary research. Other broader impacts are that the causal relations encoded for the specific creativity test cases should be of value to creativity researchers in general, and the resultant designs of case studies of oscillatory memories and antenna arrays will be of interest to individuals in cognitive neuroscience and electrical engineering.
虽然支持创造力的进化计算看起来非常有前途,但目前的方法包括人类创造力来直接指导搜索过程并取代适应度函数,因此创造力不是计算过程的一部分。该项目认为因果关系和因果推理是人类在解决问题、科学发现、发明和设计方面创造力的重要方面。本研究的主要目标是通过将因果关系作为适应度函数的一部分来开发和评估因果引导进化创造力的方法。该项目将发展对将因果推理与遗传搜索过程相结合所涉及的基本原则的理解,该过程已在过去的创造性进化系统中成功使用。本科生将被鼓励在拟议的创造性进化研究整合自己的项目。其他更广泛的影响是,编码的因果关系的具体创造力测试的情况下,应该是有价值的创造力研究人员一般,和振荡记忆和天线阵列的案例研究的结果设计将感兴趣的个人在认知神经科学和电气工程。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
数据更新时间:{{ journalArticles.updateTime }}
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
James Reggia其他文献
James Reggia的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('James Reggia', 18)}}的其他基金
ITR: Self-Organizing Collective Intelligence for Adaptive Problem-Solving
ITR:用于自适应问题解决的自组织集体智慧
- 批准号:
0325098 - 财政年份:2003
- 资助金额:
$ 20万 - 项目类别:
Continuing Grant
Presidential Young Investigator Award: Abductive Inference Models in Artificial Intelligence (Information Science)
总统青年研究员奖:人工智能中的归纳推理模型(信息科学)
- 批准号:
8451430 - 财政年份:1985
- 资助金额:
$ 20万 - 项目类别:
Standard Grant
相似国自然基金
Molecular Interaction Reconstruction of Rheumatoid Arthritis Therapies Using Clinical Data
- 批准号:31070748
- 批准年份:2010
- 资助金额:34.0 万元
- 项目类别:面上项目
相似海外基金
How do mental and physical health problems contribute to inequalities in persistent school absence? A causal mediation analysis using ECHILD
精神和身体健康问题如何导致持续缺课带来的不平等?
- 批准号:
ES/Z502509/1 - 财政年份:2024
- 资助金额:
$ 20万 - 项目类别:
Fellowship
Causal inference of oral and general health using multiple large cohorts, NDB, and hospital data
使用多个大型队列、NDB 和医院数据对口腔和一般健康状况进行因果推断
- 批准号:
23H03117 - 财政年份:2023
- 资助金额:
$ 20万 - 项目类别:
Grant-in-Aid for Scientific Research (B)
MPhil/PhD Statistics (Assessing inequality in the Criminal Justice System using novel causal inference methods and Bayesian spatial models)
硕士/博士统计学(使用新颖的因果推理方法和贝叶斯空间模型评估刑事司法系统中的不平等)
- 批准号:
2905812 - 财政年份:2023
- 资助金额:
$ 20万 - 项目类别:
Studentship
Who is most affected by bullying in academic performance? An empirical study using causal inference and machine learning
谁在学业成绩上受到欺凌的影响最大?
- 批准号:
23K01372 - 财政年份:2023
- 资助金额:
$ 20万 - 项目类别:
Grant-in-Aid for Scientific Research (C)
Innovative prediction method for for chemical-induced developmental toxicity using causal inference through machine learning.
通过机器学习进行因果推理来预测化学品引起的发育毒性的创新方法。
- 批准号:
23H03555 - 财政年份:2023
- 资助金额:
$ 20万 - 项目类别:
Grant-in-Aid for Scientific Research (B)
Using Causal Machine Learning Methods to Inform Tobacco Regulatory Science
使用因果机器学习方法为烟草监管科学提供信息
- 批准号:
10662955 - 财政年份:2023
- 资助金额:
$ 20万 - 项目类别:
Identifying causal pathways for hematuria using comprehensive omics strategies: genomics, transcriptomics, metabolomics and proteomics
使用综合组学策略识别血尿的因果途径:基因组学、转录组学、代谢组学和蛋白质组学
- 批准号:
488563 - 财政年份:2023
- 资助金额:
$ 20万 - 项目类别:
Operating Grants
Bayesian causal learning: A novel framework for drug-target discovery using Mendelian randomization on single-cell transcriptomics
贝叶斯因果学习:在单细胞转录组学上使用孟德尔随机化的药物靶点发现的新框架
- 批准号:
MR/W029790/1 - 财政年份:2022
- 资助金额:
$ 20万 - 项目类别:
Research Grant
Psychological Distress, Socioeconomic Position and Inflammatory Biomarkers Across the Life Course:Elucidating the Interplay Using Causal Inference...
整个生命过程中的心理困扰、社会经济地位和炎症生物标志物:利用因果推理阐明相互作用......
- 批准号:
2725193 - 财政年份:2022
- 资助金额:
$ 20万 - 项目类别:
Studentship
Diet and cardiovascular health across childhood and adolescence: strengthening evidence on the impact of diet using modern causal inference methods in Project Viva cohort
整个童年和青春期的饮食和心血管健康:在 Project Viva 队列中使用现代因果推理方法加强饮食影响的证据
- 批准号:
472128 - 财政年份:2022
- 资助金额:
$ 20万 - 项目类别:
Fellowship Programs














{{item.name}}会员




