AI Class Notes - 2

Notes from AI Class

Any solution goes from (0,0) state to (goal state).

  • Reasoning.

  • AI stands for positive thinking.*

  • Chess playing, alternative choices, multiple choices.

  • Humans can think simultaneously different things.

  • Machine intelligence revolution.

What is A.I?

Artificial: Produced by art. Not genuine or natural, not pertaining to

    the sense of matter.

Synonymous: Synthetic, fictitious, pretend, simulated, spurious,

    unnatural.

Antonyms: Actual, genuine, honest, real, natural, truthful and

    unaffected.

Intelligence: Endowed with a faculty of reasoning, quick of mind, well

    informed and communicative.

  • Marvin Minsky's initial writings provide a very good introduction.

  • Do plants think?

Objectives of AI?

Primary Goal: To Make the computers smart. (CS)

Secondary Goal: To understand the nature of human intelligence.(psychologist)

Entreprenuers" To make machines more useful and economical (eventually

    replace humans)

Japanese tried to create machines that will help humans when they fail.

  • Fuzzy logic Fuzzy logic is a form of many-valued logic in which the truth value of variables may be any real number between 0 and 1. It is employed to handle the concept of partial truth, where the truth value may range between completely true and completely false. By contrast, in Boolean logic, the truth values of variables may only be the integer values 0 or 1. in washing machines.

  • Inacessible to humans? Machines with intelligence needed.

Normal missiles will be shot, but missiles with intelligence have chances of

hitting the target.

Virtual reality Virtual reality (VR) is a simulated experience that employs 3D near-eye displays and pose tracking to give the user an immersive feel of a virtual world. Applications of virtual reality include entertainment (particularly video games), education (such as medical, safety, or military training) and business (such as virtual meetings). VR is one of the key technologies in the reality-virtuality continuum. As such, it is different from other digital visualization solutions, such as augmented virtuality and augmented reality. system help in designing the A.I system.

What is an A.I problem today may not be same 20 years down.

Definition:

AI is the study of how to make computers do things at which at the moment,

human beings are better.

(2) AI is the study of mental faculties through the use of computational

methods.

Questions:

1) What are our own underlying assumptions about intelligence?

2) At what level of details are we going to model and mimic intelligence?

3) What kind of tools and techniques we have at present for study of AI?

4) How will we know that we have succeeded in building an intelligent system?

5) What computers can and cannot do?

6) Can machines think?

7) Can a machine fool a human being into thinking that (s)he chatting with

another human being?

Computational methods:

  • Number crunching.

  • Heuristic programming In mathematical optimization and computer science, heuristic (from Greek εὑρίσκω "I find, discover") is a technique designed for problem solving more quickly when classic methods are too slow for finding an exact or approximate solution, or when classic methods fail to find any exact solution in a search space. This is achieved by trading optimality, completeness, accuracy, or precision for speed. In a way, it can be considered a shortcut. .

  • Automatic programming.

8) Why we think that machines cannot?

9) For that matter, do humans think? and How do we think?

Chart:

A Modern AI Lab.

    * Reasoning about objects.

    * Programming [ lisp, prolog ]

    * Architecture [ fifth generation, parallel]

    * Design and Analysis Systems [ knowledge based expert AI

      systems, decision support systems]

    * Speech and Language

    * Learning.

    * Vision and Speech

    * Robotics

Intelligent Behaviour:

Use of huristics: using some rules of thumb for deciding any of the several

alternative choices.

Huristic:

Best first search, breadth first search and depth first search.

  • Huristic should help us in dramatically reducing the search for solution in

the large problem spaces.

  • No guarantee of optimal solution.

Two approaches to Designing AI Based Computers.

Top-Down Approach

        A.I. Application

        *

    * Predicate Logic

    * Frames

    * 
        Semantic Nets
            
            
              
            
            A semantic network, or frame network is a knowledge base that represents semantic relations between concepts in a network. This is often used as a form of knowledge representation. It is a directed or undirected graph consisting of vertices, which represent concepts, and edges, which represent semantic relations between concepts, mapping or connecting semantic fields. A semantic network may be instantiated as, for example, a graph database or a concept map. Typical standardized semantic networks are expressed as semantic triples.
            
        .

    * Knowledge Representation



        A.I. Languages

    * Lisp

    * Prolog

    * Smalltalk

Bottom Up Approach

        Computing Model

    * Control Flow

    * Data Structure

    * Data



        A.I Architecture

Assignment:

To Reach IISc from your Home.

Parameters: Vehicle, Mode of transport, Map.

Time and shortest path constraints.

Between own vehicle and public transport, which one is preferable?

Knowledge:

Search Engine, algorithm is intelligence and database is knowledge.

Human information processing.

All knowledge structures are Tree Structures.

Reasoing:

Reasoning refers to the different kinds of activities:

  • Drawing conclusions from different set of facts.

  • Diagnosing possible cause of conditions.

  • Making assumption about a situation.

  • Analysis of organizing facts and data about problem

  • Solving a problem or a puzzle.

  • Arguing with a person with a particular point of view.

Classification of Reasoning activities:

Based on Degree of perception

  • Deductive reasoning.

  • Inductive reasoning.

  • Default reasoning.

Based on level of reasoning.

  • Problem level reasoning.

  • Meta level reasning.

Based on generality

  • Casual

  • Common Sense.

  • von monotonic

  • Plausible

  • special

  • Temporal

  • Reasoning systems involve the representation of information and word.

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Thanks for information.

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