乌托邦战争论——莫尔《乌托邦》中的战争观

莫尔的《乌托邦》专辟一节讲述乌托邦人的战争观。乌托邦人表面反战,却不仅有一套自己的正义战争理由,还有一套高度理性的战争行为。对这部分文本的仔细分析表明,这些论述并不严肃;相反,根据沃格林的诊断,莫尔的戏谑背后是文艺复兴时期的人文主义智识人共有的那种贪婪狂特质。在当下,更为审慎的做法是重新审视而非一味推崇文艺复兴智识人。

A NOTE ON CONDITIONAL IMPLICATION

It is well known that there exists a tight connection between nonmonotonic reasoning and conditional implication. Many researchers have investigated it from various angles. Among th em, C.Boutilier and P.Lamarre have shown that some conditional implication may b e regarded as the homology of different nonmonotonic consequence relations. In t his paper, based on the plausibility space introduced by Friedman and Halpern, w e characterize the condition logic in which conditional implication is nonmonoto nic, and this result characterizes the conditional implication which may be rega rded as the corresponding object in Meta language for nonmonotonic inference rel ations.

BACKGROUND KNOWLEDGE AND SECONDARY KNOWLEDGE BASES IN LEARNINGS YSTEMS

This paper presents the differences and relations between background knowledge and domain theories in learning systems. The roles they play during learning procedures are discussed. It is emphasized that background knowledge plays an important role in enhancing the ability of a learning system. An explanation based learning system with domain theory in primary knowledge base and background knowledge in secondary knowledge base is introduced as an example. It shows how background knowledge can be used to solve some of the problems caused by incomplete domain theory in an explanation based learning system. The system can accomplish knowledge level learning through purely deductive approach. At last the acquisition of background knowledge is briefly discussed.

Immune evolutionary algorithms with domain knowledge for simultaneous localization and mapping

Immune evolutionary algorithms with domain knowledge were presented to solve the problem of simultaneous localization and mapping for a mobile robot in unknown environments. Two operators with domain knowledge were designed in algorithms, where the feature of parallel line segments without the problem of data association was used to construct a vaccination operator, and the characters of convex vertices in polygonal obstacle were extended to develop a pulling operator of key point grid. The experimental results of a real mobile robot show that the computational expensiveness of algorithms designed is less than other evolutionary algorithms for simultaneous localization and mapping and the maps obtained are very accurate. Because immune evolutionary algorithms with domain knowledge have some advantages, the convergence rate of designed algorithms is about 44% higher than those of other algorithms.

Hand Gesture Recognition Based on Improved FRNN

The trained Gaussian mixture model is used to make skincolour segmentation for the input image sequences. The hand gesture region is extracted, and the relative normalization images are obtained by interpolation operation. To solve the proem of hand gesture recognition, Fuzzy-Rough based nearest neighbour（RNN） algorithm is applied for classification. For avoiding the costly compute, an improved nearest neighbour classification algorithm based on fuzzy-rough set theory （FRNNC） is proposed. The algorithm employs the represented cluster points instead of the whole training samples, and takes the hand gesture data＇s fuzziness and the roughness into account, so the campute spending is decreased and the recognition rate is increased. The 30 gestures in Chinese sign language alphabet are used for approving the effectiveness of the proposed algorithm. The recognition rate is 94.96%, which is better than that of KNN （K nearest neighbor）and Fuzzy- KNN （Fuzzy K nearest neighbor）.

Intelligence in Clothing Pattern CAD System

It analyzes three recognition methods for five elements,i.e.dot,line,loop,clothing pattern as well as characters,and also applies intelligent points and tangential curve in the CAD system to solve the problem complained by CAD users.It indicates that recognition of five elements is a foundational technique of intelligence in clothing pattern CAD system.Common functions in operation state such as move,rotation,flip,measure,should precede ones in element state as dot,line,and pattern.Moreover,it is realized that the less skill the CAD user needs,the more the CAD software is high-tech.

Online RGB-D person re-identification based on metric model update

Person re-identification （re-id） on robot platform is an important application for human-robot- interaction （HRI）, which aims at making the robot recognize the around persons in varying scenes. Although many effective methods have been proposed for surveillance re-id in recent years, re-id on robot platform is still a novel unsolved problem. Most existing methods adapt the supervised metric learning offline to improve the accuracy. However, these methods can not adapt to unknown scenes. To solve this problem, an online re-id framework is proposed. Considering that robotics can afford to use high-resolution RGB-D sensors and clear human face may be captured, face information is used to update the metric model. Firstly, the metric model is pre-trained offline using labeled data. Then during the online stage, we use face information to mine incorrect body matching pairs which are collected to update the metric model online. In addition, to make full use of both appearance and skeleton information provided by RGB-D sensors, a novel feature funnel model （FFM） is proposed. Comparison studies show our approach is more effective and adaptable to varying environments.

A PRELIMINARY STUDY OF EXPERT SYSTEM FOR MINING UNDER STRUCTURES

The expert system MUST (Mining Under Structures) shown in this paper and established by the authors is a preliminary expert system to solve the policy-making problems for mining under structures by means of computers instead of humanbeing. Based on the experience of relative experts,the authors established a knowledge base about the minings under structures,researched into reasonable method to simulate thinking processes of human experts when they are solving the problems, established the network of an expert system and named it ' MUST system' . MUST system uses the method of the structural system analysis approach. A kind of methods of Turbo Prolog and Fortran 77 language alternations is designed to meet the needs of exchange information within the MUST system. Based on this kind of methods MUST system has been constructed and realised on IBM-PC computer. For verifying the correctness, suitability and reliablity of MUST system,some practical examples of minings under structures were tentatively solved using MUST system,whose results are satisfactory.

The Wisdom in the Apology of Plato

The concept of ＂wisdom＂ which Plato elaborates in his Apology is analyzed here. In doing so, we describe how Socrates, once declared by the Oracle to be ＂the wisest man,＂ starts to analyze what wisdom actually means. In trying to contradict the Oracle, Socrates mixes with different social groups including politicians, poets, and artisans. He discovers that none of them possess a real understanding or awareness of what wisdom actually is. Thus, Socrates concludes that he must be the wisest man because, ＂he knows that he does not know.＂ This ignorantia docta is a type of humanistic knowledge

Cognitive Emotion Model for Eldercare Robot in Smart Home

Based on the smart home and facial expression recognition, this paper presents a cognitive emotional model for eldercare robot. By combining with Gabor filter, Local Binary Pattern algorithm(LBP) and k-Nearest Neighbor algorithm(KNN) are facial emotional features extracted and recognized. Meanwhile, facial emotional features put influence on robot's emotion state, which is described in AVS emotion space. Then the optimization of smart home environment on the cognitive emotional model is specially analyzed using simulated annealing algorithm(SA). Finally, transition probability from any emotional state to a state of basic emotions is obtained based on the cognitive reappraisal strategy and Euclidean distance. The simulation and experiment have tested and verified the effective in reducing negative emotional state.

Implementing Semantic Deduction of Propositional Knowledge in an Extension Multi-layer Perceptron

The paper presents an extension multi-laye r p erceptron model that is capable of representing and reasoning propositional know ledge base. An extended version of propositional calculus is developed, and its some properties is discussed. Formulas of the extended calculus can be expressed in the extension multi-layer perceptron. Naturally, semantic deduction of prop ositional knowledge base can be implement by the extension multi-layer perceptr on, and by learning, an unknown formula set can be found.

Analysis of the Story-Line Behind Selected Hausa Proverbs

Proverbs which are short witty traditional oral expressions handed down from generation to generation as a common heritage is also believed to be true expressions of the Hausa people＇s philosophy. This philosophy is clad in different ways by the people as they are continuously at work to give meanings to their creative activities. Proverbs are one of the most relevant expressions of human wisdom and knowledge of nature, psychology, and reality for the Hausa people of Northern Nigeria; however, the images that are presented in the proverbs are culturally defined and they may differ from place to place, as well as from generation to generation. Proverbs are capable of a variety of meanings, according to how and when they are used. These findings have revealed that many popular and interesting Hausa proverbs tell a condensed story; these stories give vivid illustrations which help the hearer understand the proverbs. In this paper, the author attempts a deep intellectual analysis into the story-lines behind the emergence of some selected Hausa proverbs, with a view to comprehending and propagating embedded ideas and cultural principles or philosophies that may be relevant for contemporary social usage.

Speech Recognition Technology Applied to Intelligent Mobile Navigation System

The capability of human_computer interaction reflects the intelligent degree of mobile navigation system.The navigation data and functions of mobile navigation system are divided into system commands and non_system commands in this paper.And then a group of speech commands are abstracted.This paper applies speech recognition technology to intelligent mobile navigation system to process speech commands and does some deep research on the integration of speech recognition technology with mobile navigation system.The navigation operation can be performed by speech commands,which makes human_computer interaction easy during navigation.Speech command interface of navigation system is implemented by Dutty ++ Software,which is based on speech recognition system _Via Voice of IBM.Through navigation experiments,navigation can be done almost without keyboard,which proved that human_computer interaction is very convenient by speech commands and the reliability is also higher.

Challenges and opportunities:from big data to knowledge in AI 2.0

In this paper, we review recent emerging theoretical and technological advances of artificial intelligence （AI） in the big data settings. We conclude that integrating data-driven machine learning with human knowledge （common priors or implicit intuitions） can effectively lead to explainable, robust, and general AI, as follows： from shallow computation to deep neural reasoning; from merely data-driven model to data-driven with structured logic rules models; from task-oriented （domain-specific） intelligence （adherence to explicit instructions） to artificial general intelligence in a general context （the capability to learn from experience）. Motivated by such endeavors, the next generation of AI, namely AI 2.0, is positioned to reinvent computing itself, to transform big data into structured knowledge, and to enable better decision-making for our society.