《智取生辰纲》中的“智”与“不智”

近二十年关于《智取生辰纲》的研究,主要集中从情节、人物、环境等方面解读“智取”。本文从“整本书阅读”的角度重新审视这一情节,发现《智取生辰纲》有“智”的一面,主要体现在如何蒙骗杨志以及让杨志喝酒的双重智计上;然而《智取生辰纲》的“智”有很大的片面性,其中又有“不智”的一面,主要表现在谋划之时所出现的种种疏漏上。从整本书阅读的视角中,才能洞察《智取生辰纲》中“智”与“不智”的统一。

智者啊,你何以如此不智?

翻开《存在与时间》，品味那意蕴悠长的章句，参悟那高山仰止的哲思，徘徊沉吟，俯仰其中的洞天世界。而后不禁叹息：既为这超乎群哲的智慧而发出赞叹，又为这智者的不智而痛惜叹惋——是的，他一生可以说仅有这一次不智，但这个污点却如同沾了水的墨迹一般，四散开去，最后将他的一切成就镀上了黑色。

烛之武的“智”与“不智”

凡是读过《烛之武退秦师》者,无不为烛之武临危受命、不计个人安危且善于辞令的智勇形象所折服。确实,在大兵压境、国家危在旦夕之时,一个须发皆白、走路都巍颤颤的老者,孤身一人深入虎穴高谈阔论,最终劝退强敌,单凭这份勇气,都已是千古绝唱了,至于凭三寸之舌＂不战而屈人之兵＂的智慧,更令古今多少号称＂英雄豪杰＂者五体投地、望尘莫及啊!

“知不道”和“不知道”

目前在官话方言区内说“知不道”者约两亿人。“知不道”来自“智不到”,至南宋写作“知不到”或“知不道”,意思是“认识不到”。“知不道”和“不知道”不仅来历、结构均不相同,而且本义完全不同,引申义亦不尽相同。

A NEW EVIDENCE UPDATING RULE BASED ON CONDITIONAL EVENT

Updating or conditioning a body of evidence modeled within the DS framework plays an important role in most of Artificial Intelligence (AI) applications. Rule is one of the most important methods to represent knowledge in AI. The appearance of uncertain reasoning urges us to measure the belief of rule. Now,most of uncertain reasoning models represent the belief of rule by conditional probability. However,it has many limitations when standard conditional probability is used to measure the belief of expert system rule. In this paper,AI rule is modelled by conditional event and the belief of rule is measured by conditional event probability,then we use random conditional event to construct a new evidence updating method. It can overcome the drawback of the existed methods that the forms of focal sets influence updating result. Some examples are given to illustrate the effectiveness of the proposed method.

A navigation method based on POMDP for smart wheelchair in uncertain environments

A navigation method based on the partially observable markov decision process （POMDP） for smart wheelchairs in uncertain environments is presented in this paper. The design key factors for the navigation system of a smart wheelchair are discussed. A kinematics model of the smart wheelchair is given, and the model and principle of POMDP are introduced. In order to respond in uncertain local environments, a novel navigation methodology based on POMDP using the sensors perception and the user＇s joystick input is presented. The state space, the action set, the observations and the sensor fusion of the navigation method are given in detail, and the optimal policy of the POMDP model is proposed. Experimental results demonstrate the feasibility of this navigation method. Analysis is also conducted to investigate performance evaluation, advantages of the approach and potential generalization of this paper.

Intelligent Integrated Control of Underactuated Mechanical Systems with Second-order Nonholonomic Constraints

This paper describes an intelligent integrated control of an acrobot, which is an underactuated mechanical system with second-order nonholonomic constraints. The control combines a model-free fuzzy control, a fuzzy sliding-mode control and a model-based fuzzy control. The model-free fuzzy controller designed for the upswing ensures that the energy of the acrobot increases with each swing. Then the fuzzy sliding-mode controller is employed to control the movement that the acrobot enters the balance area from the swing-up area. The model-based fuzzy controller, which is based on a Takagi-Sugeno fuzzy model, is used to balance the acrobot. The stability of the fuzzy control system for balance control is guaranteed by a common symmetric positive matrix, which satisfies linear matrix inequalities.

为何我越努力越失败?

案例：小烨是个非常聪明且用功的孩子,之前他的成绩很优秀,然而出人意料,他的中考成绩并不如人意,为了证明自己只是一次失误,他更加努力,可是几次月考下来成绩不升反降。期中考试时,更是落到了班里的后几名。

A lightweight authentication scheme with user untraceability

With the rapid growth of electronic commerce and associated demands on variants of Internet based applications,application systems providing network resources and business services are in high demand around the world.To guarantee robust security and computational efficiency for service retrieval,a variety of authentication schemes have been proposed.However,most of these schemes have been found to be lacking when subject to a formal security analysis.Recently,Chang et al.(2014) introduced a formally provable secure authentication protocol with the property of user-untraceability.Unfortunately,based on our analysis,the proposed scheme fails to provide the property of user-untraceability as claimed,and is insecure against user impersonation attack,server counterfeit attack,and man-in-the-middle attack.In this paper,we demonstrate the details of these malicious attacks.A security enhanced authentication scheme is proposed to eliminate all identified weaknesses.

Leader-Following Consensus for Discrete-Time Multi-Agent Systems with Parameter Uncertainties Based on the Event-Triggered Strategy

In this paper, the leader-following consensus for discrete-time nmlti-agent systems with parameter uncertainties is investigated based on the event-triggered strategy. And the parameter un- certainty is assmned to be norm-bounded. A consensus protocol is designed based on the event-triggered strategy to make the multi-agent systems achieve consensus without continuous communication among agents. Each agent only needs to observe its own state to determine its own triggering instants under the triggering function in this paper. In addition, a sufficient condition for the existence of the event- triggered consensus protocol is derived and presented in terms of the linear matrix inequality. Finally, a numerical example is given to illustrate to efficiency of the event-triggered consensus protocol proposed in this paper.

Intelligent diagnosis of jaundice with dynamic uncertain causality graph model

Jaundice is a common and complex clinical symptom potentially occurring in hepatology, general surgery, pediatrics, infectious diseases, gynecology, and obstetrics, and it is faidy difficult to distinguish the cause of jaundice in clinical practice, especially for general practitioners in less developed regions. With collaboration between physicians and artificial intelligence engineers, a comprehensive knowledge base relevant to jaundice was created based on demographic information, symptoms, physical signs, laboratory tests, imaging diagnosis, medical histories, and risk factors. Then a diagnostic modeling and reasoning system using the dynamic uncertain causality graph was proposed. A modularized modeling scheme was presented to reduce the complexity of model construction, providing multiple perspectives and arbitrary granularity for disease causality representations. A ＂chaining＂ inference algorithm and weighted logic operation mechanism were employed to guarantee the exactness and efficiency of diagnostic rea- soning under situations of incomplete and uncertain information. Moreover, the causal interactions among diseases and symptoms intuitively demonstrated the reasoning process in a graphical manner. Verification was performed using 203 randomly pooled clinical cases, and the accuracy was 99.01% and 84.73%, respectively, with or without laboratory tests in the model. The solutions were more explicable and convincing than common methods such as Bayesian Networks, further increasing the objectivity of clinical decision-making. The promising results indicated that our model could be potentially used in intelligent diagnosis and help decrease public health expenditure.