AI in the 21st century - With historical reflections

The discipline of Artificial Intelligence (AI) was born in the summer of 1956 at Dartmouth College in Hanover, New Hampshire. Half of a century has passed, and AI has turned into an important field whose influence on our daily lives can hardly be overestimated. The original view of intelligence as a computer program - a set of algorithms to process symbols - has led to many useful applications now found in internet search engines, voice recognition software, cars, home appliances, and consumer electronics, but it has not yet contributed significantly to our understanding of natural forms of intelligence. Since the 1980s, AI has expanded into a broader study of the interaction between the body, brain, and environment, and how intelligence emerges from such interaction. This advent of embodiment has provided an entirely new way of thinking that goes well beyond artificial intelligence proper, to include the study of intelligent action in agents other than organisms or robots. For example, it supplies powerful metaphors for viewing corporations, groups of agents, and networked embedded devices as intelligent and adaptive systems acting in highly uncertain and unpredictable environments. In addition to giving us a novel outlook on information technology in general, this broader view of AI also offers unexpected perspectives into how to think about ourselves and the world around us. In this chapter, we briefly review the turbulent history of AI research, point to some of its current trends, and to challenges that the AI of the 21st century will have to face. © Springer-Verlag Berlin Heidelberg 2007.

AI in locomotion: Challenges and perspectives of underactuated robots

This article discusses the issues of adaptive autonomous navigation as a challenge of artificial intelligence. We argue that, in order to enhance the dexterity and adaptivity in robot navigation, we need to take into account the decentralized mechanisms which exploit physical system-environment interactions. In this paper, by introducing a few underactuated locomotion systems, we explain (1) how mechanical body structures are related to motor control in locomotion behavior, (2) how a simple computational control process can generate complex locomotion behavior, and (3) how a motor control architecture can exploit the body dynamics through a learning process. Based on the case studies, we discuss the challenges and perspectives toward a new framework of adaptive robot control. © Springer-Verlag Berlin Heidelberg 2007.

Nonlinear Optical Properties of AI-Doped nc-Si-SiO_2 Composite Films

The nonlinear optical properties of Al-doped nc-Si-SiO_2 composite films have been investigated using the time-resolved four-wave mixing technique with a femtosecond laser. The off-resonant third-order nonlinear susceptibility is observed to be 1.0 × 10~(-10) esu at 800nm. The relaxation time of the optical nonlinearity in the films is as short as 60fs. The optical nonlinearity is enhanced due to the quantum confinement of electrons in Si nanocrystals embedded in the SiO_2 films. The enhanced optical nonlinearity does not originate from Al dopant because there are no Al clusters in the films.

Nd-AI双金属活性体的活性部位及其对共轭双烯烃聚合机理的研究

稀土催化剂活性体对双烯烃配位聚合的研究已有很多报道,使用催化剂活性体对双烯烃聚合机理的研究比以前所用的多组分混合物的催化体系显然具有很大的优越性。本文利用NdCl_3·3TBP和Ndel_3·3P_(350)配合物与Al(i-Bu)_3体系所得活性体合成了共轭双烯烃低聚物,用IR、~(13)C-NMR光谱研究了这些低聚物分子的链端结构,从而推测活性体的活性部位组成和聚合机理。

迟缓爱德华氏菌(Edwardsiella tarda) LuxS/AI-2群体感应系统研究

从患病牙鲆中分离出迟缓爱德华氏菌株TX1，经报告菌株检测发现TX1有AI-2活性。用梯度PCR和Genome walking的方法克隆了TX1 luxS基因，将luxS基因在大肠杆菌DH5α中表达，证明其具有功能活性。在TX1中，luxS的表达与AI-2的活性基本是一致的，二者均受生长时期和生长条件的调节，即在glucose存在的条件下luxS表达和AI-2活性升高，而在高温条件下luxS表达和AI-2活性降低。glucose对AI-2活性以及luxS表达的影响经过荧光定量PCR，启动子活性检测，AI-2活性检测以及凝胶滞缓等一系列的实验证实是由cAMP-CRP复合物介导的，该复合物可以通过与luxS启动子相互作用而抑制luxS的表达。RNA干扰表明，TX1中luxS表达被干扰以后，对细菌产生了多方面的影响，包括：(1) 降低AI-2水平；(2) 降低细菌的生长能力；(3) 降低Ⅲ型分泌系统相关基因的表达水平以及生物膜的形成能力；(4) 减弱细菌毒力。外源AI-2的添加可以回复Ⅲ型分泌系统相关基因的表达水平以及生物膜的形成，但是并不能修复生长状况，表明LuxS在TX1中具有双重功能，即参与细胞代谢以及群体感应信号传导。基于LuxS/AI-2群体感应系统对细菌毒力的重要性，设计并筛选了一个该系统的阻遏因子5411。Pull-down实验证明5411可以和LuxS特异性结合。研究表明5411在TX1中表达导致细菌毒力显著下降。将5411克隆至牙鲆共生菌FP3中，发现5411可以被分泌到胞外并能被TX1吸收。将表达5411的共生菌导入牙鲆，发现其能够有效阻遏TX1对牙鲆的侵染。 这些结果表明：(1) TX1中AI-2的活性受控于LuxS，而后者则受生长时期和生长条件的调控；(2) luxS的正常表达对于细菌的正常生长和侵染是必需的；(3) LuxS/AI-2群体感应系统调控Ⅲ型分泌系统相关毒力因子的表达；(4) 通过阻遏LuxS/AI-2群体感应系统来抑制病原菌侵染是一种具有潜力的新型病害防控方法。

实时控制中对人工智能(AI)的挑战是什么

近年来,人工智能(AI)技术及其应用吸引了许多研究者,然而人们有时对其期望过高,所以弄清楚 AI 所能提供的实际能力,以及如何解决 AI 中的关键——知识获取问题是必要的。这样,我们就可以在应用中,按照对象的实际来选择人工智能方法或其他方法。

The 1990 AI Fair

This year, as the finale to the Artificial Intelligence Laboratory's annual Winter Olympics, the Lab staged an AI Fair ??night devoted to displaying the wide variety of talents and interests within the laboratory. The Fair provided an outlet for creativity and fun in a carnival-like atmosphere. Students organized events from robot boat races to face-recognition vision contests. Research groups came together to make posters and booths explaining their work. The robots rolled down out of the labs, networks were turned over to aerial combat computer games and walls were decorated with posters of zany ideas for the future. Everyone pitched in, and this photograph album is a pictorial account of the fun that night at the AI Fair.

Tudur Aled ai cant yn dda om barn i: Cywydd Cymod Wmffre ap Hywel ap Siancyn o Ynysymaengwyn a'i Geraint

Williams, G. (2007). Tudur Aled ai cant yn dda om barn i: Cywydd Cymod Wmffre ap Hywel ap Siancyn o Ynysymaengwyn a'i Geraint. Ll?n Cymru. 30, pp.57-99. RAE2008