new overview of artificial intelligence

7/30/2019 New Overview of Artificial Intelligence

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INTERNATIONAL JOURNAL ofACADEMIC RESEARCH Vol. 4. No. 2. March, 2012NEW OVERVIEW OF ARTIFICIAL INTELLIGENCE

Hussein H. Owaied

Department of Computer Science, Middle East University, Amman (JORDAN)[email protected]

ABSTRACT

This paper presents a new overview for the term Artificial Intelligence. The philosophy behind this newoverview based on only one ayah from the Holy Quran which is ayah 78 in Surah Al-Bees. The definition ofartificial intelligence and new direction of future research are presented. The architecture of knowledge-basedsystem has been developed as mimic to the proposed functional model of human system. The new ArtificialIntelligence wills concentrate in soft computing for creating the intelligent agents which will be used for the buildingof the Intelligent Machines. In this paper the research areas for the new artificial intelligence are proposed.

Key words: Artificial Intelligence, Expert System, Knowledge-based Systems, Knowledge Representation,Problem Solving Methodology, and Searching Techniques

1. INTRODUCTION

In 7 December 2009 David L. Chandler, MIT News Office [2] announce about, the Rethinking artificial intelli-gence, Broad-based MIT project aims to reinvent AI for a new era. By going back and fixing mistakes, researchershope to produce coprocessors for the human mind. He said that, The field of artificial intelligence research,founded more than 50 years ago, seems too many researchers to have spent much of that time wandering in thewilderness, swapping hugely ambitious goals for a relatively modest set of actual accomplishments.

Clay Dillow [3] comment about this news and said that After 50 years and countless dead ends, incrementalprogress, and modest breakthroughs, arti ficial intelligence researchers are asking for a do-over. Therefore the MindMachine Project (MMP) began at MIT, a patchwork team of two dozen academics, students and researchers,intends to go back to the discipline's beginnings, rebuilding the field from the ground up.

Most people know the term artificial intelligence concerning about how to build intelligent machine. Thismachine should have certain capabilities such as, behave as human being, smart, and solving unstructured andcomplex problems as human does. For these capabilities to be reached, as in [4] declare that the machine shouldhave the facilities of recognition, analysis, deduction, and induction.

Since most of the definitions of Artificial intelligence (AI) are concerning the human intelligence, but in realityall the creature have in some way an intellect behavior, such as human, animals, insects and so on. In this paperwill concentrate on only one creature which is the human and the reason for that; is human created by Allah as themost valuable and intellectual creature. Because Allah mocked everything in the sky and the earth to him in orderto do his job. Since one of the most important capabilities of the intelligence machine is behave as human,therefore will considering the human intellect forms and the functional model of human system in this paper.

2. WHY IT IS ARTIFICIAL INTELLIGENCE

In this section we will explain the capabilities which are mention in more details to give the reader betterunderstanding view of them as follows:

A. Behave as Human Beings: This means the machine must do all the activities that human does duringhis life, such as expert systems where a trial is made to embody experts knowledge in certain domain in acomputer program for carrying out some task, vision for dealing with three dimension world, speech to replace thekeyboards for dealing with computerized systems, perception, recognition, analysis, deduction, induction, and soon. All these activities are soft computing.

B. Smart: This term usually has many meaning in the English language so the meaning concern withintelligent machine is psychologically means giving pleasure to the user, therefore we must design a machine thatgive pleasure through the facilities are available in all sorts of the multimedia equipments. In this regard designspecial multimedia equipments which are needed by human to give him pleasure during the use of computersystem.

C. Solving Unstructured and Complex Problems: In this context human usually solve algorithmic andnon-algorithmic problem and most problems are non algorithmic, therefore we have to consider methodologies forrepresenting the non algorithmic problems in a form that enable us to develop a problem solving methods. Thiscapability is the most important and the most of the pioneers of AI, are concentrating about it, such as Luger in hisbook "artificial intelligence: structure and strategies for complex problems solving [5].

From the above understanding views all the capabilities that were considered are non touchable things

which can't be manufactured in factories but can be simulated. Therefore we call it Artificial Intelligence notIndustrial Intelligence. In this context we can give an understandable definition of AI that considers all capabilitiesmentioned above, that will be discussed in this paper.


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INTERNATIONAL JOURNAL ofACADEMIC RESEARCH Vol. 4. No. 2. March, 2012In order to understand Artificial Intelligence concept, a clear and recent definition was mentioned by [6] as

Artificial Intelligence is the concept of study and research for finding relationships between cognitive science andcomputation theories in order to represent these relationships as either data structures, search techniques, prob-lem solving methods or representation forms for knowledge and the final goal of AI is to build an intelligentmachine, with another benefit which is better understanding of human thinking.

Artificial Intelligence has been highlighted researched extensively, trying to build machines that have somesort of intelligence. As [7] discussed to build such machines should have certain capabilities such as behaves like a

human being, smart, problem solver of unstructured and complex problems as human does, understandslanguages, learner, and able to reason and analyze data and information, and so on.

The previous definition was built on the fact that for a machine to be intelligent it should be smart andproblem solver. Smart can be defined as everything gives pleasure and happiness to humans, through the facilitiesavailable in all sort of multimedia equipments.

In the other hand, the intelligent machine to be problem solver for unstructured and complex problem, itshould be like the human where humans usually solve algorithmic and non algorithmic problems and most prob-lems are non algorithmic, this capability is the most important and most of the pioneers of A.I. are concentrating onthem like [5] and [8].

For more than 50 years, the concepts and applications of intelligent robots (Intelligent Machine) have beenexplored by the researchers in the field of Robots and AI. These intelligent robots are often modeled by what wesee when we look into a mirror or what we as humans can perform. Over the years a variety of intelligent robotshave been described from game playing robots to novel industrial robots to mobile sensor guided robots. Theseintelligent robots are remarkable combinations of mechanisms, sensors, computer controls and power sources.

Each component, as well as the proper interfaces among and between the components is essential to a successfulrobust intelligent robot.As defined by [9] Cognition is the understanding, acquisition, and processing of knowledge, or, more

loosely, thought processes.However cognitive science refers to the interdisciplinary study of the acquisition and use of knowledge. It

includes as contributing disciplines; artificial intelligence, psychology, linguistics, philosophy, anthropology,neuroscience, and education [10].

Since knowledge is the human brain soul, in order to solve problems and communicate with others, theneeds of applying the human brain model on the intelligent robot increased by the demand of building an intelligentrobot. The knowledge based system must be applied by covering one of its fields, i.e. receiving, thinking andstoring knowledge. Therefore the next sections will be functional model of human system architecture, and presenttwo scenarios for creating the functional model of human system and how the functional model of human systemworks respectively.

3. FUNCTIONAL MODEL OF HUMAN SYSTEM ARCHITECTURE

All discussion will be based on the Holy Quran, Allah mentioned in the Quran and especially the Surah Al-Bees 78, Allah brought you out from the wombs of your mothers knowing nothing, and gave you hearing and sightand hearts that ye may give thanks. So all human born without knowledge, they can do nothing, and then givethem the five senses. These are vision, hearing, touching, sniffing, and tasting and through these senses humansgather their knowledge, as seen in the direction of arrow in the left-hand side of Fig. 1.

Fig.1. Functional Model of Human SystemArchitecture

These five senses are considered as five information processing systems; which are information processingsystem for vision, information processing system for hearing, information processing system for touching,

information processing system for smelling, and finally information processing system for tasting. All these systemsare depending on the representation of the relative knowledge about the information processing. The mainfunctions of human inference engine are; first choosing the right form for knowledge representation in long term


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INTERNATIONAL JOURNAL ofACADEMIC RESEARCH Vol. 4. No. 2. March, 2012memory; second are the processes of representing the knowledge in long term memory; third are the processes forclarifying the ambiguity of the new knowledge, through calling an existing knowledge from the long term memory,and fourth is the processes of retrieving the adequate knowledge from long term memory according to theassertions given to solve relative problem in a certain domain. All of the mentioned functions (of human inferenceengine) have their own roles in the construction of human career and it is very important. So we believe that theinference engine as the following non touchable activities which are: willing and needs, vision, Incentives, hobbies,and the effect of environment. Therefore we believe any human can't have any job without the knowledge of doing

that job, and the knowledge can't be well represented in his long term memory without the influence of thecombination of the above activities.

4. SCENARIO FOR CONSTRUCTION FUNCTIONAL MODEL OF HUMAN SYSTEM(HUMAN CHARACTERISTICS CAREER)

Usually all humans get their knowledge through the communications with the environment via their senses(vision, hearing, touching, tasting, and sniffing). Then the inference engine will start choosing the appropriateknowledge representation form and then present it in the long term memory if there is no ambiguity, but if there isan ambiguity the inference engine calling the prior knowledge (existing knowledge in long term memory) for theclarification and then present it in long term memory.

So the most importance part of the functional human system is the inference engine since it is responsiblefor knowledge representation in the long term memory and as mention in section 3, the human inference enginenon touchable activities which are: willing and needs, vision, Incentives, hobbies, and the effect of environment.

5. SCENARIO FOR SOLVING PROBLEMS BY FUNCTIONAL MODEL OF HUMAN SYSTEM

Human solving problems usually starts from the communications with the environment by gathering theassertion about the problem, then the inference engine calling the prior knowledge (existing knowledge in long termmemory) associatively. According to this scenario we believe that nobody can do any job without the knowledge ofdoing that job which exists in his long term memory accumulated during the construction of his functional modelwhich mentioned in section 4. Also we believe that nobody can have normal life without job and his life willterminated in any moment, usually suicides, in certain types of suicides and we give advice for all human to have ajob.

6. KNOWLEDGE-BASED SYSTEM

The design and implementation of knowledge based system will be from bottom to up according to thedirection of arrow in the left side of Fig.2 as mimic the functional model of human system. Therefore the implement-

tation starts from the knowledge base and then proposing an inference engine and a user interface which aresuitable to the knowledge base representation forms.

The most important phase in building knowledge based system is building the knowledge base. Theimplementation of knowledge base depends on the representation forms of the knowledge and usually there aremany forms (Rule base, Case base, Frame base, Semantic nets, Logic forms and so on) used by human which aremay be applied [11].

Since human inference engine were the non touchable activities which are: willing and needs, vision,Incentives, hobbies, and the effect of environment, which are mention in section 3, implemented in the knowledge-based system as problem solving method, search technique, and reasoning agent. The user interface may employQuestion and Answer, Menu-driven, Natural language, or graphics interface styles.

Fig. 2. Structure of Knowledge-Based System

7. HUMAN INTELLIGENT FORMS

Since the term intelligence is fog and misunderstood and cant be clearly defined, therefore we will try toassume certain forms to represent this term, these are:


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INTERNATIONAL JOURNAL ofACADEMIC RESEARCH Vol. 4. No. 2. March, 2012A. Abduction: the logic suggested by [12], can be viewed as logic of exploratory data analysis. For Peirce

abduction is the firstness (existence, actuality); deduction, the secondness (possibility, potentiality); and induction,the thirdness (generality, continuity). Abduction plays the role of generating new ideas or hypotheses; deductionfunctions as evaluating the hypotheses; and induction is justifying of the hypothesis with empirical data.

Abduction is to look for a pattern in a phenomenon and suggest a hypothesis and is hypothesis generations.In exploratory data analysis, after observing some surprising facts, exploit them and check the predicted valuesagainst the observed values and residuals. Although there may be more than one convincing patterns, the

abducted is the only those which are more plausible. Peirce argued that animals have the instinct to do the rightthings without struggling, so humans, as a kind of animal, also have the innate ability to make the right decisionintuitively. One of the assumptions of Peircean philosophical system is anti-Cartesian skepticism. DesCartesdoubted everything, even his own existence [13].

In his view, knowledge originates from doubts and questioning. Peirce in1868 rejected the Cartesiantradition by arguing, "We cannot begin with complete doubt. Rather he ensured what Hegelians deny--we don'thave to be certain of everything in order to know something. Therefore the knowledge does not emerge out ofpure logic instead; it is a historical and social product.

For Peirce a reasoned should apply abduction, deduction and induction altogether in order to achieve acomprehensive inquiry. So at the stage of abduction, the goal is to explore the data, find out a pattern, and suggesta plausible hypothesis with the use of proper categories; deduction is to build a logical and testable hypothesisbased upon other plausible premises; and induction is the approximation towards the truth in order to fix our beliefsfor further inquiry.

B. Induction: We mean by induction that human can discover new facts and rules from previously knowncertain facts. For example: in sales man problem the sales man depend on the facts he has to follow a certain pathnot another since he try to develop a decision tree of all the possibilities. We can notice from the above examplenot all people have this capability in one degree.

C. Deduction: This means that human being from previously known rules and their applications for solvinggiven problems and assertions can apply it for certain circumstances to discover new facts and rules. But not allpeople have the same degree of this capability of calling the right rule according to the given assertions.

D. Analogical reasoning: The analogical reasoning capabilities vary from one human to another.it is basedon previously known system and the problem solving rules within the system. So the analogical reasoning meansfinding relationships with the known system and new system in order to solve the new unknown problems withinthe new system. Therefore, through these relationships the problem for the new system can be solved.

E. Heuristic search: The heuristic search is a search technique most commonly used by human in order to

find the faster solution but not necessarily the optimal solutions. This technique depends on the heuristic informa-tion which usually founded in the problem space to lead the search technique processes.

The process of human common sense is depending on the power of induction and analogical reasoning, sothese two human capabilities are varying from one human to another. Therefore the common sense differs fromone person to another accordingly. All people have common sense and always use it in their problem solving butsometime they solve the problem adequately and sometime solve it but not given an adequate solution. Althoughsometime the same people from the same background in specific domain facing some problems, then they providedeferent solutions according to their common sense even though they have the same assertions about theproblems.

There are many reasons for this situation since that human is a system acting analogically not sequentiallyduring solving problems and affect and effect by many factors in his environment. First, we might ask whether thereis any particular methodology, among the many that exist, that stands out as being particularly relevant to human-level AI. AI researchers have several overlapping objectives. Among these are: to build systems that aid humans inintellectual tasks; to build agents that can function autonomously in circumscribed domains; to build a general

science of intelligence as manifested in animals, humans, and machines; and to build versatile agents with human-level intelligence or beyond.

So there are some important considerations for those working toward building human level AI agents.Among the alternative methodologies, in no particular order, are those that stress the importance of the fol lowingpoints which should be considered in the new Artificial Intelligence. The new Artificial Intelligence wills concentratein soft computing for creating the intelligent agents which will be used for building the Intelligent Machines. Thefollowing are the research areas for the new A.I.

1. Logical Representation and Reasoning2. Neural Networks3. Probabilist ic Representations and Inference4. Object-Oriented Representations5. Evolutionary Computation6. Modeling Human, Animal and their Cognition Behavior Scenarios7. Heuristic Search Methodology

8. Emerge Phenomena from the Interaction between agents with each other9. The Types of Environments10. Knowledge Engineering


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INTERNATIONAL JOURNAL ofACADEMIC RESEARCH Vol. 4. No. 2. March, 20128. CONCLUSION

This paper is based on just one Surah of the Holy Quran which it is Surah Al-Bees ayah 78. The followingpoints can conclude:

1. Study the Holy Quran intensively because all the knowledge exists and will be grasped.2. A new direction for studying the Artificial Intelligence (AI) which should concentrate on studying human

in more deeply how solve problems.3. Concentrate on soft computing in term of intelligent agent as a knowledge-based system.4. The researchers should consider any human function as an intelligent agent.5. Development of new problem solving methodology and new searching techniques which are based on

the study of human behavior.6. The researchers should note that why all the existing books are consternating on problem solving

methodology and searching techniques.7. The new Artificial Intelligence wills concentrate in soft computing for creating the intelligent agents will

used for building the Intelligent Machines.

REFERENCES

1. The Holy Quran, Surah Al-Bees, ayah 78.2. Clay Dillow, 2009, MIT Plans to Rebuild Artificial Intelligence from the Ground Up.

http://www.popsci.com/technology/article/2009-12/scientists-collaborate-rebuild-artificial-intelligence-ground.3. David L. Chandler, 2009, Rethinking artificial intell igence, MIT News Office, December 7, 2009.4. Avron Barr, Paul R. Cohen and Edward A. Feigenbaum (Jan 1990), the Handbook of Artificial

Intelligence, Volume IV.5. LUGER G., 1999, Artificial Intelligence: Complex Problem Solving Methodologies", Addison-Wesley,

Fourth Edition1999.6. Hussein H. Owaied and Mahmoud M. Abu-A'ra "Functional Model of Human System as Knowledge

Based System", Proceeding of the 2007 International Conference on Information and KnowledgeEngineering,, June 25-28,2007 Las Vegas Nevada, USA pp.158-161.

7. Hussein H. Owaied, Mahmoud Malek Abu-A'ra, Hazim A. Farhan, 2010, An Application ofKnowledge-based System, IJCSNS International Journal of Computer Science and NetworkSecurity, VOL.10 No.3, March 2010, pp 208-213.

8. Winston P.H., 1992, Artificial Intelligence, Addison Wesley, 3rd Edition 1992.9. Stuart-Hamilton, Ian, 1995, Dictionary of developmental psychology, Published London: Jessica

Kingsley.10. Eysenck H. J. (1990). Biological dimensions of personality. In L. A. Pervin (Ed.), Handbook of

personality: Theory and research (pp. 244-276). New York: Guilford.11. Hussein H. Owaied, 2011, Design and implementation of shell expert system, International Journal

of Academic Research, Volume 3. No. 6. November 30, 2011.12. Peirce C. S., Reasoning and the Logic of Things, The Cambridge Conference Lectures of 1898,

Kenneth Laine Ketner, ed., intro., and Hilary Putnam, intro., commentary, Harvard, 1992, 312 pages.13. Ren Descartes, John Cottingham and Bernard Williams (Apr 26, 1996) Descartes: Meditations on

First Philosophy: With Selections from the Objections and Replies. (Cambridge Texts in the Historyof Philosophy).


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