AI & KBS

AI & KBS

Overview

* A brief history of Artificial Intelligence (AI) - requirements of KBS

* Introduction to Knowledge-Based Systems (KBS) - definition - architecture - development tools* Examples of some KBS * Characteristics of KBS

AI & KBS

1. The Evolution of AI (1) The request of an intelligent machine - early robots ---- electro-mechanical devices - later robots ---- use computers, ‘dumb’

limited and pre-specified tasks - ideal robots ---- intelligent machine combines the memory

accuracy, and speed of computers with the intelligence and flexibility of humans.

AI - Computer programs that undertake tasks that, if done by people would be described as requiring intelligence.

* Can computers think? - Turing Test

Imitation game - machine mistaken for a human“Computing machinery and intelligence”, Alan Turing, 1950

AI & KBSWall

In the Turing test a human communicates with an unseen respondent througha terminal, not knowing if the respondent is a person or a machine. If the tester mistakes computer answers for human answers, the computer successfully passes the Turning test.

AI & KBS

ELIZA

• Developed by MIT 1966• Called ELIZA after Shaws play - it could be taught to speak increasing well• It picked up words from its conversational partner• Transform this into a canned responseELIZA’s opening statement (appears on the terminal screen):

Do you have any problems?Human: Yes. I am unhappy. (types response on the terminal screen)ELIZA: Why are you unhappy?Human: My friend is mean to me.ELIZA: Tell me about your friend. (Rogerian Psychoanalyst)

It could fool people into thinking it was a real person but it containedno intelligence.

AI & KBS

(2) Game playing - early AI emphasis - Board games: chess, checkers, & 16-puzzle - No ambiguity in representation of the board configuration - Rules generate large search space: require heuristics

Move1 - X

2 - O

3 - X

4 - O

5 - X

Tic-Tac-Toe game

AI & KBS

(3) Theorem proving

- The proving of mathematical theorems by a computer program

- Theorems automatically proven from a given set of axioms - Theorems & axioms expressed in logic and logical inferences applied - First theorem prover developed in mid-50s but breakthrough in 1960s - Breakthrough came after introduction of Resolution inference rule

AI & KBS

Theorem proving -Resolution

All Irish are Europeans.

Dave is a Irish.

Therefore, Dave is a European

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(4) Problem solving - GPS (General Problem Solver) focus on systems with general capability for solving different types of problems - Problem represented in terms of initial state, wished-for final state (goal) and a set of legal transitions to transfer states into new states - Using states & operators, GPS generates sequence of transitions that transform initial state into final state

AI & KBS

- Problems with GPS:

* efficiency in choosing path to reach the goal * GPS did not use specific info about problem at hand in selection of state transition * GPS examined all states leading to exponential time complexity * breakthrough in AI towards more specialised problem-solving system, i.e.,

Knowledge-based systems

AI & KBS

(5) Other AI fields - a tree representation

AI & KBS

(6) KBS as real-world problem solvers - Problem-solving power does not lie with smart reasoning techniques nor clever search algorithms but domain dependent real-world knowledge - Real-world problems do not have well-defined solutions - Expertise not laid down in algorithms but are domain dependent rules-of-thumb or heuristics (cause-and-effect) - KBS allow this knowledge to be represented in computer & solution explained

AI & KBS

2. Knowledge-based Systems: A definition

- A system that draws upon the knowledge of human experts captured in a knowledge-base to solve problems that normally require human expertise. - Heuristic rather than algorithmic - Heuristics in search vs. in KBS

general vs. domain-specific - Highly specific domain knowledge - Knowledge is separated from how it is used

KBS = knowledge-base + inference engine

AI & KBS

3. KBS Architecture

End-userinterface

Inferenceengine

Knowledge-base

Explanation

ConclusionsExpertiseRecommendationsfor action

Queries

Facts Heuristics, etc.

Knowledge-representationschema

AI & KBS

(1) Knowledge-base

Knowledge-base

HeuristicsHypothesis Rules

Facts

Processes

Events

DefinitionsRelationships

Attributes

Objects

AI & KBS

(2) Knowledge representation formalisms & Inference

KR Inference* Logic Resolution principle* Production rules backward (top-down, goal directed)

forward (bottom-up, data-driven)* Semantic nets & Frames Inheritance & advanced reasoning* Case-based Reasoning Similarity based

AI & KBS

(3) KBS tools - Shells

- Consist of KA Tool, Database & Development Interface

- Inductive Shells - simplest - example cases represented as matrix of known data (premises) and resulting effects (conclusions) - matrix converted into decision tree or IF-THEN statements - examples selected for the tool

- Rule-based shells - simple to complex - IF-THEN rules

AI & KBS

- Special purpose shells - specifically designed for particular types of problems - restricted to specialised problems

-Scratch - require more time and effort - no constraints like shells - shells should be investigated first

- Hybrid shells - sophisticate & powerful - support multiple KR paradigms & reasoning schemes - generic tool applicable to a wide range

AI & KBS

4. Some example KBSs (1) DENDRAL (chemical)

- Pioneering work developed in 1965 for NASA at Stanford University by Buchanan & Feigenbaum- DENDRAL infers the molecular structure given mass spectral data- Traditional method of generate-and-test, difficulty: millions of possible structures might be generated to account for data- Experts used rules-of-thumb to weed-out structures that are unlikely to account for the data - Encoded this expertise & produced program which performed as well as an expert chemist

AI & KBS

(2) MYCIN (medicine)

- Developed in 1970 at Stanford by Shortcliffe- Assist internists in diagnosis and treatment of infectious diseases: meningitis & bacterial septicemia- When patient shows signs of infectious disease, culture of blood and urine set to lab (>24hrs) to determine bacterial species- Given patient data (incomplete & inaccurate) MYCIN gives interim indication of organisms that are most likely cause of infection & drugs to control disease- Drug interactions & already prescribed drugs taken into account- Able to provide explanation of diagnosis (limited)

AI & KBS

(3) XCON/RI (computer)

- Configures DEC’s VAX, PDP11 and VAX- DEC offers the customer a wide choice of components when purchasing computer equipment, so that client achieves a custom-made system- Given the customer’s order, configuration is made, perhaps involving component replacement or addition- Problem: information subject to rapid change & configuring a computer system requires skills and effort- Since 1981, XCON with XSEL assists DEC agents in drawing up orders.

AI & KBS

(4) DRILLING ADVISOR (industry)

- Developed in 1983 by Teknowledge for oil company to replace human drilling advisor- Problem:drill bits becoming stuck- Difficulty: lack of subsurface information on location & condition on end of drill - (scarcity) expert examines rock pieces, mud, lubricant brought up by drilling to determine cause- Drilling Advisor uses geological site information, conditions of problem, historical information about other problems experienced in the past - Provide recommendation to correct problem & advice on how to change current practices to avoid problem

AI & KBS

(5) Human Resource Management HRM facilitates the most effective use of

employees to achieve organisational and individual goals

HRM KBS forms part of overall strategy (includes DSS & EIS)

KBS helps decision making for HRM managers with heuristic knowledge in unstructured & semi-structured problems (job placement & pay rises)

Using semantic nets & Prolog, illustrates use of KBS in HR planning, recruiting, compensation & labour-management relations

(see Human resource management expert systems technology, Byun & Suh, ES, May 94, 11:2)

AI & KBS

5. Typical tasks of KBS

(1) Diagnosis - To identify a problem given a set of symptoms or malfunctions. e.g. diagnose reasons for engine failure(2) Interpretation - To provide an understanding of a situation from available information. e.g. DENDRAL(3) Prediction - To predict a future state from a set of data or observations. e.g. Drilling Advisor, PLANT(4) Design - To develop configurations that satisfy constraints of a design problem. e.g. XCON(5) Planning - Both short term & long term in areas like project management, product development or financial planning. e.g. HRM

AI & KBS

(6) Monitoring - To check performance & flag exceptions. e.g., KBS monitors radar data and estimates the position ofthe space shuttle(7) Control - To collect and evaluate evidence and form opinions on that evidence. e.g. control patient’s treatment(8) Instruction - To train students and correct their performance. e.g. give medical students experience diagnosing illness (9) Debugging - To identify and prescribe remedies for malfunctions. e.g. identify errors in an automated teller machine network and ways to correct the errors

AI & KBS

6. Advantages & Limitations

(1) Advantages

- Increase availability of expert knowledgeexpertise not accessibletraining future experts

- Efficient and cost effective- Consistency of answers- Explanation of solution- Deal with uncertainty

AI & KBS

(2) Limitations

-Lack of common sense-Inflexible, Difficult to modify- Restricted domain of expertise- Lack of learning ability- Not always reliable

AI & KBS

Overview

- Traditional AI & its limitations for real-world problem solving- KBS emergence in 60’s emphasis on specific domain-knowledge rather than GPS separation of knowledge and reasoning - KBS basic components: knowledge-base, inference engine & user-interface- Examples- Advantages & limitations