计算机科学国家重点实验室

State Key Laboratory of Computer Science


2019年开放课题申请工作正式开始

2019年开放课题申请工作正式开始,课题和经费管理使用参见《计算机科学国家重点实验室开放课题管理办法》(2012年修订)。

1.申请人资格:凡是具有博士学位或中级以上职称的国内、外从事计算机科学理论和软件研究的科研人员均可以向实验室申请开放基金课题,项目执行期间每年保证在实验室工作一段时间。

2.时间及要求:申请者须填写《计算机科学国家重点实验室开放课题基金申请书》,申请截止日期:2019年4月14日。课题经实验室学术委员会审查,室务委员会批准,评审结果将于2019年6月通知申请者本人及所在单位。

3.申请书寄至:北京海淀区中关村南四街4号计算机科学国家重点实验室(邮政编码:100190)。来函请注明“开放课题”。申请书电子版发至: zli (at) ios.ac.cn。

4.联系人: 张丽,电话:010-62661616,传真:010-62661627

详情请点击”实验室主页 | 学术 | 开放课题“。

计算机科学国家重点实验室招收2017年推免研究生

计算机科学国家重点实验室正在招收2017年入学的推免研究生,欢迎有志于在计算机科学理论与软件方法与技术等方面取得国际一流成绩的同学加盟。

实验室招收推免研究生的方式是:同学与导师先进行前期的沟通,然后合适者参加包括笔试、面试等在内的考核,经教育小组讨论后,报软件所审核。

欢迎同学们积极与实验室的导师进行沟通联系。

图灵奖获得者Leslie Lamport博士访问计算机科学国家重点实验室

2015年10月26日下午, 2013年ACM图灵奖获得者、微软研究院首席研究员Leslie Lamport博士到软件所访问,与计算机科学国家重点实验室的科研人员进行学术座谈。座谈会由林惠民院士主持。
Lamport博士详细回答了实验室科研人员关于并发程序演进条件等问题的提问,听取了实验室科研人员在概率模型检测、混成系统验证与合成、自动推理、可线性化检测等方面的工作介绍。

Lamport博士对实验室在并发数据结构可线性化检测方面的最新研究成果表现出浓厚的兴趣,双方就相关技术细节,特别是其中基于分支互模拟关系的检测方法,进行了深入、细致地讨论。

唐稚松先生学术思想研讨会

The Evolutionary Benefit of Recombination

2015/08/28

Speaker: Andy Lewis-Pye (London School of Economics, UK)    www.aemlewis.co.uk/

Time: 28th August 2015, 15:00

Venue: Seminar Room (334), Level 3, Building 5,

Institute of Software, Chinese Academy of Sciences (CAS),

4 Zhongguancun South Fourth Street, Haidian District, Beijing 100190

(The address in Chinese and a map are in the attached.)

Abstract:

The question as to why most higher organisms reproduce sexually has remained open despite extensive research, and has been called “the queen of problems in evolutionary biology”. Given the connections to optimisation problems more generally, and especially to issues in genetic algorithms, this is also a question which has recently attracted interest in the computer science community. Theories dating back to Weismann have suggested that the key must lie in the creation of increased variability in offspring, causing enhanced response to selection. Rigorously quantifying the effects of assorted mechanisms which might lead to such increased variability, and establishing that these beneficial effects outweigh the immediate costs of sexual reproduction has, however, proved problematic. In recent work with Montalban, which I shall discuss in this talk, we introduced an approach which does not focus on particular mechanisms, influencing factors such as the fixation of beneficial mutants or the ability of populations to deal with deleterious mutations, but rather tracks the entire distribution of a population of genotypes as it moves across vast fitness landscapes. In this setting simulations now show sex robustly outperforming asex across a broad spectrum of finite or infinite population models. Concentrating on the additive infinite populations model, we are able to give a rigorous mathematical proof establishing that sexual reproduction acts as a more efficient optimiser of mean fitness, thereby solving the problem for this model. Some of the key features of this analysis carry through to the finite populations case.

No background knowledge will be required for the talk.

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