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Different Types of K.B.S. Expert Systems Mimic the reasoning processes of human experts Example Applications include - Diagnostic systems (Doctor, Technician, car mechanic etc.) Identification systems (Materials spillage, Bacterial agent identifier, etc.) Decision Support systems

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Different types of k b s
Different Types of K.B.S.

  • Expert Systems

  • Mimic the reasoning processes of human experts

  • Example Applications include -

  • Diagnostic systems

  • (Doctor, Technician, car mechanic etc.)

  • Identification systems

  • (Materials spillage, Bacterial agent identifier, etc.)

  • Decision Support systems

  • (Planning, scheduling, design systems)


Different types of k b s1
Different Types of K.B.S.

  • Expert System Definitions

  • “A computer program that uses symbolic knowledge and inference to reach conclusions” (Dictionary of AI, D. Mercadal, 1990)

  • “A computer system which can act as a human expert within one particular field of knowledge” (P.Smith, 1990)


Different types of k b s2
Different Types of K.B.S.

  • Expert System Definitions

  • “An expert system is regarded as the embodiment within the computer of knowledge based component from an expert skill, in such a form that the system can offer intelligent advice or take an intelligent decision about a processing function. A desirable additional characteristic, which many would consider fundamental, is the capability of the system, on demand, to justify it’s own line of reasoning in a manner directly intelligible to an enquirer. The style adopted to attain these characteristics is rule based programming”

  • (Formal definition agreed by the British Computer Society’s specialist group on Expert Systems)


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Different Types of K.B.S.

Expert

Database

Acquisition Module

Acquires knowledge

Knowledge base

Representation of knowledge

Core of ES

Inference engine

Reasons using knowledge

Explanatory interface

The human window

User


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Different Types of K.B.S.

  • Expert Systems are suitable when -

  • The problem is important to business

  • The expertise required is available and stable

  • The knowledge required is scarce

  • The problem is recurrent

  • The problem is the right level of difficulty

  • The domain is well defined and of manageable size

  • The solution depends on logical reasoning, not “common sense” or general knowledge


Different types of k b s5
Different Types of K.B.S.

Expert

Database

Acquisition Module

Medical knowledge

Empty K. B.

Car mechanic’s knowledge

Core of ES

Design knowledge

Inference engine

Explanatory interface

User


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Different Types of K.B.S.

The Brain

Pattern recognition Association Complexity Noise tolerant

The Machine

Calculation Precision Logic


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Different Types of K.B.S.

The Von Neumann architecture uses a single processing unit

- tens of millions of operations per second - Absolute arithmetic precision

The brain

- uses many slow, unreliable processors acting in parallel


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Different Types of K.B.S.

  • Features of the Brain -

  • 10 Billion neurones

  • Average several thousand connections each

  • Hundreds of operations per second

  • Low reliability

  • Die frequently and are never replaced

  • Problems are compensated for by massive parallelism


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Different Types of K.B.S.

The structure of neurones


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Different Types of K.B.S.

  • The Structure of Neurones

  • A neurone only “fires” if it’s input signal exceeds a threshold level within a short time period

  • Synapses vary in strength

    • Good connections allow a large signal

    • Slight connections only allow a weak signal

    • Synapses can be either exhibitory or inhibitory


Different types of k b s11

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Different Types of K.B.S.

A Classic Artificial Neuron


Different types of k b s12
Different Types of K.B.S.

Neural Network Taxonomies

Supervised Training

Unsupervised Training

Perceptron/

Multi-Layer

Perceptron

Others

Kohonen

Self-Organising

Map

ART 2

Radial

Basis

Function

Bayesian

Methods


Different types of k b s13

Output Values

Input Signals (External Stimuli)

Different Types of K.B.S.

  • Multilayer Perceptron

Output Layer

Adjustable

Weights

Input Layer


Different types of k b s14
Different Types of K.B.S.

  • Types of Layer

  • The Input Layer

    • Introduces input values into the network

    • No activation function or other processing

  • The Hidden Layer(s)

    • Perform classification of features

    • Two hidden layers are sufficient to solve any problem

    • More layers may do better

  • The output Layer

    • Functionally just like the hidden layers

    • Outputs are passed on to the outside world


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Different Types of K.B.S.

  • Back Propagation

  • Calculate output error for each pattern

  • Adjust weights into output nodes to reduce the error

  • Propagate errors backwards towards input layer

  • Repeat iteratively until satisfied

  • Presenting a complete set of training data is called an epoch


Different types of k b s16
Different Types of K.B.S.

  • Building a Network

  • Encode problem in a form suitable for Neural Networks

  • Gather training data

  • Define network architecture

  • train network

  • Use the trained network on new problems


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Different Types of K.B.S.

  • Network Architecture

  • Number of layers and units per layer

  • Input and output will be defined by the problem

  • Hidden layers defined by the designer

  • Decide how many training patterns to use


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Different Types of K.B.S.

  • Overtraining

  • A sufficient number of nodes can classify any training set exactly

  • May have poor generalisation ability

  • Cross Validation

  • Typically, 50% of training patterns are not used

  • These are used to test the network’s abilities by determining a validation error

  • Training is stopped when the validation error starts to go up


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Different Types of K.B.S.

  • Example Applications

  • Engine Management

  • Engine behaviour is influenced by a large number of parameters such as -

    • temperature at various points

    • Fuel/air mixture

    • lubricant viscosity

    • etc. etc...


Different types of k b s20
Different Types of K.B.S.

  • Example Applications

  • Signature Recognition

  • All signatures are different

  • There are structural similarities which are difficult to quantify

  • Neural networks can recognise features of signatures with a high level of accuracy

  • They can consider the speed at which a signature was written, as well as the shape


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Different Types of K.B.S.

  • Example Applications

  • Stock Market Prediction

  • “Technical Trading” refers to trading based solely on known statistical parameters (I.e. previous price)

  • Neural networks have been used to attempt to predict changes in prices

  • The success of neural networks here is difficult to assess due to secrecy


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Different Types of K.B.S.

  • Example Applications

  • Mortgage Assessment

  • Neural networks can be used to assess lending risks

  • Artificial networks have produced a 12% reduction in errors compared with human experts


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Different Types of K.B.S.

  • Case Based Reasoning

  • Case Based Reasoning (CBR) provides an automated method for storing experience and reusing it to make decisions in the future

  • Example Applications

  • Help desk applications

  • Application of the Law


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Different Types of K.B.S.

  • Implementing C.B.R.

  • Collect the important features which define each new case presented to the system

  • Retrieve past cases matching these features most closely

  • Use the matching case to solve the problem

  • If no match found find an alternative solution and record both problem and solution

  • If multiple solutions are found then resolve any ambiguities

  • Multiple solutions may sometimes be acceptable


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Different Types of K.B.S.

  • Implementing C.B.R.

  • The process is crucially dependent on 3 things -

  • Appropriate methods for indexing cases using their key attributes

  • Efficient mechanisms for retrieving cases given a set of index values

  • Good presentation of the information to the user


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