Consciousness,intentionality and intelligence: some foundational issues for artificial intelligence

Three fundamental questions concerning minds are presented. These are about consciousness, intentionality and intelligence. After we present the fundamental framework that has shaped both the philosophy of mind and the Artificial Intelligence research in the last forty years or so regarding the last two questions, we turn to consciousness, whose study still seems evasive to both communities. After briefly illustrating why and how phenomenal consciousness is puzzling, a theoretical diagnosis of the problem is proposed and a framework is presented, within which further research would yield a solution. The diagnosis is that the puzzle stems from a peculiar dual epistemic access to phenomenal aspects (qualia) of our conscious experiences. An account of concept formation is presented such that both the phenomenal concepts (like the concepts RED and SWEET) and the introspective concepts (like the concepts EXPERIENCING RED and TASTING SWEET) are acquired from a firstperson perspective as opposed to the third-person one (the standard concept formation strategy about objective features). We explain the first-person perspective in information-theoretic and computational terms: Nature (the Art whereby God hath made and governes the World) is by the Art of man, as in many other things, so in this also imitated, that it can make an Artificial Animal. For seeing life is but a motion of Limbs, the beginning whereof is in some principall part within; why may we not say, that all Automata (Engines that move themselves by springs and wheels as doth a watch) have an artificiall life? For what is the Heart, but a Spring; and the Nerves but so many Strings; and the Joynts, but so many Wheeles, giving motion to the whole Body, such as was intended by the Artificer? Art goes yet further, imitating that Rationall and most excellent worke of Nature, Man. (Hobbes 1651, p. 81) So declared Thomas Hobbes in 1651 in the Introduction to his well-known work, Leviathan, published one year after Réne Descartes' death. Descartes was also interested in mechanical explanations of bodily processes and organic life. In fact, on the basis of his neuroanatomical and physiological studies, as well as philosophical arguments, Descartes had already argued that human and animal bodies could be mechanically understood as complicated and intricately designed machines (Descartes 1664). What differentiated Descartes from Hobbes lay in his belief that human beings, unlike non-human animals, were not merely bodies; they were unions of material bodies and immaterial souls. The immaterial soul was necessary for Descartes to explain the peculiar capacities and activities of the human mind. As such, materialist mechanical explanations could never be sufficient to account for the whole human being.     

人工智能伦理体系:基础架构与关键问题

全球范围内针对人工智能伦理准则的讨论已达成基本共识。在此基础上，本文进一步研究4个关键问题:人工智能伦理体系的运行机制问题、人工智能伦理准则的场景落地问题、人工智能伦理风险的预测判别问题，以及人工智能伦理对重大社会问题综合创新的支撑机制问题。这些问题超越了人工智能伦理准则的范围，却是一种完整、有效的人工智能伦理体系所必须解答的。本文的主要贡献是对这4个问题提出一套建议方案。     

Development of an expert system for preliminary risk assessment of existing concrete dams

The paper presents an expert system to assist in the field inspection of existing concrete dams within the context of a preliminary risk assessment. The paper describes the engineering knowledge and reasoning required to conduct a deterministic field evaluation of the structural stability of the dam. The symptoms and failure modes identified by the expert system along with the required knowledge and procedures are organized in a structured knowledge tree. The instantiation of the frames and firing of the rules for each consultation traces part of the inference tree contained in the structured knowledge tree. Interaction between nearly decomposable problems are executed with metaknowledge procedures, shared rule groups, and active values. Examples are provided.     

人工智能在海参养殖专家系统中的应用

设计并实现了海参养殖智能信息平台,以促进海参养殖的信息化,提高生产效率。通过人工神经网络找出影响海参生长和成活的规律,利用遗传算法进行全局搜索,找出能够使成活率和生长率最高的参数组合,使用最小二乘法限定遗传算法的搜索范围,使用模拟退火算法进行遗传算法的变异操作,进行局部搜索。系统投入运行,经过专家鉴定,系统计算结果合理。     

An expert system framework for a CIM based quality inspection system

With today's competitive marketplace moving toward a goal of lean, error free manufacturing a need for technological change in quality decision making has arisen. One approach to this new “quality” standard involves tying quality analysis to the theory of Computer Integrated Manufacturing (CIM). In this paper a model of such a system is presented including the application of an expert system to enhance dimensional tolerancing and data analysis in quality control. Our expert system will also serve a dual role as a technological link to a CIM environment through the use of IGES computer aided design data.     

A comparative survey of artificial intelligence applications in finance: artificial neural networks, expert system and hybrid intelligent systems

Nowadays, many current real financial applications have nonlinear and uncertain behaviors which change across the time. Therefore, the need to solve highly nonlinear, time variant problems has been growing rapidly. These problems along with other problems of traditional models caused growing interest in artificial intelligent techniques. In this paper, comparative research review of three famous artificial intelligence techniques, i.e., artificial neural networks, expert systems and hybrid intelligence systems, in financial market has been done. A financial market also has been categorized on three domains: credit evaluation, portfolio management and financial prediction and planning. For each technique, most famous and especially recent researches have been discussed in comparative aspect. Results show that accuracy of these artificial intelligent methods is superior to that of traditional statistical methods in dealing with financial problems, especially regarding nonlinear patterns. However, this outperformance is not absolute.     

An artificial intelligence system of trouble diagnosis for aircraft engines

:Reported here is about the trouble diagnosis system for AN-24 aircraft engine which has been realized by inputting the experiences of the repair mechanics or experts of the engine as a computer software.The system is composed of following four sections which are called “model” ; a phenomena model, an inference model, a learning model, and an interpretation model.Therefore, the system is called as “model diagnosis system”. These four models are relatively independent which makes parallel operation, easy debugging, and addition of new knowledge possible.

The experience of the engine experts has been stored initially to outer knowledge base in the computer. Intermidiate knowledge which arises on the process of the inference is treated at inner knowledge base. The inner knowledge base adopts a blackboard structure. This makes the system not only able to diagnose the vague preconditioned reason, but also to diagnose the unpreconditioned one by learning. The validity of the system was proved from some experiments.     

Business applications of artificial intelligence knowledge based expert systems

Business organizations have shown a broad range of interest in knowledge based systems, including not only expert systems but also advisory systems, to assist experts in their tasks, and checklist systems to support clerical workers. These interests can be displayed by mapping existing and planned systems along two axes: the role a system in intended to serve and the complexity of the problem environment with which the system must deal. The maps provide a vehicle for understanding the rationales employed by businesses in making decisions to build knowledge based systems. They also provide a basis for understanding what currently is practical, and what barriers exist that will limit the future growth of business knowledge based systems.     

Advanced issues in artificial intelligence and pattern recognition for intelligent surveillance system in smart home environment

During the last decades, many researchers in image processing and AI community have been focused on developing image and video analysis and understanding. However, despite their extensive efforts on these, there are still several significant challenges such as robust object segmentation and tracking, motion feature extraction, context modeling, and machine learning algorithms. Therefore, more advanced related issues should be taken into account. We have selected nine research papers whose topics are strongly related to the intelligent surveillance system in smart home environment.     

An artificial intelligence approach for medical picture analysis

This paper reports a first experiment to apply the expert system techniques to image understanding. The expertise comes from two sides: the picture processing domain and the context of the application.Preliminary results are presented on the labellisation of the blood vessels on a digital angiography. Part of this work has been supported under Esprit project P26 “Advanced algorithms and architectures for speech and image processing”.     

An expert system for sorting

Abstract: Sorting an internal list is an indispensable requirement in numerous data processing applications, and many algorithms have been devised for accomplishing those tasks. Furthermore, it is fairly simple to derive order of magnitude of effort measures for particular sorting strategies, and within classes of equivalent theoretical power, practice has shown which algorithms prevail in which circumstances. Thus there is a useful background for testing a system's ability to learn which problem solving technique should be applied in a given instance, for the expert knowledge is rather concise and structured and facilitates comparison to machine decisions. The paper describes the construction of such a system and analyzes the results.     

ESOM: An expert system for multicriteria scheduling

There exist situations in operations scheduling where the parameters of the scheduling decision are nonquantifiable, or appear as nonnumerical entries in a database. Scheduling techniques based on numerical algorithms may be difficult to use in such situations. In many service industries, the nonnumerical character arises from constraints or preference parameters associated with service tasks, service agents, and the business operation itself. The agent to task assignment problem is one of satisfying multiple objectives, by taking into account the various constraints and preferences inherent in such problems. In this paper, we describe the development of an expert system prototype called ESOM, that aims to automate the assignment decision process of a childcare referral agency. We discuss some key research issues pertaining to service scheduling in general, and to the childcare assignment problem in particular. ESOM provides useful guidelines to future researchers and practitioners interested in building expert systems for service scheduling. We demonstrate assignments made by our prototype through an application scenario.     

Urban planning and artificial intelligence: The Urbys system

The subject of this paper is the complementary use of both a data base and an expert system in the analysis of urban areas in territorial planning.After a discussion of urban reasoning, this paper then states the fundamental principles of the URBYS system: —storage of the urban planner's knowledge; —the use of this knowledge by the expert system to assist in decision-making; —output of information from the urban data base to the expert system.A special effort was made to facilitate the use of this system and its closeness to the expert method by an easy modification of URBYS' knowledge without the overall coherence being affected.     

人工智能在传感器领域的应用

人工智能作为一门正在迅速发展的学科，已被广泛地应用于传感器领域。人工智能与传感器技术相结合构成新型的智能传感器，提高了传感器的智能水平，是智能传感器发展的一个方向。简要介绍了人工智能的四个分支：模糊逻辑、人工神经网络、专家系统、遗传算法在传感器领域的应用。     

An expert system for process planning

Fully integrated manufacturing systems, the ultimate goal of today's production engineering research, cannot be realized without automated process planning systems. A knowledge-based expert system incorporating heuristic algorithms as well as analytical and empirical models and which can thus provide a partial replacement for human expertise is the only key to automated process planning.This paper presents an attempt to develop an expert system for automatic process planning using artificial intelligence. In this system, a structural database was incorporated with a knowledgebase for the execution of rules. The programs developed are user-friendly and highly interactive. They allow dialog between the system and the user and require only that the operator answer questions in a familiar workshop language.     

An expert system for respirator selection

A Respirator Selection Expert System (RSES) is described which assists the user in selection of a respirator for a specific application. In addition to determining the minimum class of respirator which should be used by following the NIOSH Respirator Decision Logic, RSES also provides all necessary calculations, data for common industrial contaminants and on-line reference material.     

Logic, probability theory, and artificial intelligence - Part I: the probabilistic foundations of logic

Many AI researchers have come to be dissatisfied with approaches to their discipline based on formal logic. Various alternatives are often suggested, including probability theory. This paper investigates the intimate connection between probability theory and various logics. We show that probability theory, broadly conceived, may be used as a formal semantics for virtually any monotonic logic. Thus, rather than being seen as competing, it is more appropriate to view formal logics as very special cases of probability theory, usually special cases that are computationally more tractable than the more general theory. Thus, probability theory and logic should be seen as complementary. Viewing probability theory in this abstract way may help to shed light on various recalcitrant problems in AI. De nombreux chercheurs dans le domaine de l'intelligence artificielle manifestent une certaine insatisfaction vis-à-vis certaines approches basées sur la logique formelle. Diverses solutions sont souvent proposées, y compris la théorie des probabilityés. Cet article analyse la relation intime entre la théorie des probabilités et diverses logiques. Il est démontré que la théorie des probabilityés, conçue de manière générale, peut ětre utilisée comme une sémantique formelle pour presque toute logique monotonique. Au lieu de percevoir les logiques formelles comme étant en opposition, il est plus approprié de les considérer comme des cas trés spéciaux de la théorie des probabilityés, habituellement plus traitables au niveau calcul que la théorie plus générate. Par conséquent, la théorie des probabilityés et la logique doivent ětre percues comme des éléments complémentaires. Le fait de considérer la théorie des probabilityés d'une manière abstraite peut contribuer à la compréhension de divers problèmes ardus dans le domaine de l'intelligence artificielle.     

USFKAD: An expert system for partial differential equations

The computation of the solution, by the separation of variables process, of the Poisson, diffusion, and wave equations in rectangular, cylindrical, or spherical coordinate systems, with Dirichlet, Neumann, or Robin boundary conditions, can be carried out in the time, Laplace, or frequency domains by a decision-tree process, using a library of eigenfunctions. We describe an expert system, USFKAD, that has been constructed for this purpose.

Program summary

Title of program:USFKADCatalogue identifier:ADYN_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADYN_v1_0Program obtainable from: CPC Program Library, Queen's University of Belfast, N. IrelandLicensing provisions:noneOperating systems under which the program has been tested: Windows, UNIXProgramming language used:C++, LaTeXNo. of lines in distributed program, including test data, etc.: 11 699No. of bytes in distributed program, including test data, etc.: 537 744Memory required to execute with typical data: 1.3 MegabytesDistribution format: tar.gzNature of mathematical problem: Analytic solution of Poisson, diffusion, and wave equationsMethod of solution: Eigenfunction expansionsRestrictions concerning the complexity of the problem: A few rarely-occurring singular boundary conditions are unavailable, but they can be approximated by regular boundary value problems to arbitrary accuracy.Typical running time:1 secondUnusual features of the program: Solutions are obtained for Poisson, diffusion, or wave PDEs; homogeneous or nonhomogeneous equations and/or boundary conditions; rectangular, cylindrical, or spherical coordinates; time, Laplace, or frequency domains; Dirichlet, Neumann, Robin, singular, periodic, or incoming/outgoing boundary conditions. Output is suitable for pasting into LaTeX documents.