Evaluation of Information
Systems
Complexity Metrics and Models
INFO 630
Glenn Booker
1
Lecture #7
INFO 630
Origin
Complexity metrics were developed
by computer scientists and software
engineers
Strongly based on empirical (real
world) measurement, with
Module 2
Problem Solving using Search(Single agent search)
Version 1 CSE IIT, Kharagpur
Lesson 5
Informed Search Strategies-I
Version 1 CSE IIT, Kharagpur
3.1 Introduction
We have outlined the different types of search strategies. In the earlier chapter w
Module 2
Problem Solving using Search(Single agent search)
Version 1 CSE IIT, Kharagpur
Lesson 4
Uninformed Search
Version 1 CSE IIT, Kharagpur
2.4 Search
Searching through a state space involves the following: A set of states Operators and their costs St
Module
2
Problem Solving
using Search(Single agent search)
Version 1 CSE IIT, Kharagpur
2.1 Instructional Objective
The students should understand the state space representation, and gain familiarity
with some common problems formulated as state space sea
Module 1
Introduction
Version 1 CSE IIT, Kharagpur
Lesson 2
Introduction to Agent
Version 1 CSE IIT, Kharagpur
1.3.1 Introduction to Agents
An agent acts in an environment.
Percepts
Agent
Environment Environment
Actions
An agent perceives its environment
Module 1
Introduction
Version 1 CSE IIT, Kharagpur
1.1 Instructional Objectives
Understand the definition of artificial intelligence Understand the different faculties involved with intelligent behavior Examine the different ways of approaching AI Look
Problem Solving, Problem Spaces
and Problem Characteristics
1
Problem Representation in AI
Before a solution can be found, the prime
condition is that the problem must be very
precisely defined. The most common
methods of problem representation in AI
are:
Module 2
Problem Solving using Search(Single agent search)
Version 1 CSE IIT, Kharagpur
Lesson 6
Informed Search Strategies-II
Version 1 CSE IIT, Kharagpur
3.3 Iterative-Deepening A*
3.3.1 IDA* Algorithm
Iterative deepening A* or IDA* is similar to iterat
Module
3
Problem Solving
using Search(Two agent)
Version 1 CSE IIT, Kharagpur
3.1 Instructional Objective
The students should understand the formulation of multi-agent search and in detail
two-agent search.
Students should b familiar with game trees.
Give
Module 6
Knowledge Representation and Logic (First Order Logic)
Version 1 CSE IIT, Kharagpur
Lesson 15
Inference in FOL - I
Version 1 CSE IIT, Kharagpur
6.2.8 Resolution
We have introduced the inference rule Modus Ponens. Now we introduce another inferenc
Module 6
Knowledge Representation and Logic (First Order Logic)
Version 1 CSE IIT, Kharagpur
Lesson 14
First Order Logic - II
Version 1 CSE IIT, Kharagpur
6.2.5 Herbrand Universe
It is a good exercise to determine for given formulae if they are satisfied/
Module 6
Knowledge Representation and Logic (First Order Logic)
Version 1 CSE IIT, Kharagpur
6.1 Instructional Objective
Students should understand the advantages of first order logic as a knowledge representation language Students should be able to conv
Module
5
Knowledge
Representation and
Logic
(Propositional Logic)
Version 1 CSE IIT, Kharagpur
Lesson
12
Propositional Logic
inference rules
Version 1 CSE IIT, Kharagpur
5.5 Rules of Inference
Here are some examples of sound rules of inference. Each can
Module
5
Knowledge
Representation and
Logic
(Propositional Logic)
Version 1 CSE IIT, Kharagpur
5.1 Instructional Objective
Students should understand the importance of knowledge representation in intelligent
agents
Students should understand the use of f
Module 4
Constraint satisfaction problems
Version 1 CSE IIT, Kharagpur
Lesson 10
Constraint satisfaction problems - II
Version 1 CSE IIT, Kharagpur
4.5 Variable and Value Ordering
A search algorithm for constraint satisfaction requires the order in which
Module 4
Constraint satisfaction problems
Version 1 CSE IIT, Kharagpur
4.1 Instructional Objective
The students should understand the formulation of constraint satisfaction problems Given a problem description, the student should be able to formulate it
Module 3
Problem Solving using Search(Two agent)
Version 1 CSE IIT, Kharagpur
Lesson 8
Two agent games : alpha beta pruning
Version 1 CSE IIT, Kharagpur
3.5 Alpha-Beta Pruning
ALPHA-BETA pruning is a method that reduces the number of nodes explored in Min
Turing Test
The "standard interpretation" of the Turing Test, in which
player C, the interrogator, is tasked with trying to determine
which player - A or B - is a computer and which is a human.
The interrogator is limited to using the responses to written
STATISTICAL REASONING
Himanshi
Lpu
SYMBOLIC REASONING UNDER
UNCERTAINTY
Story so far
We have described techniques for reasoning with a complete,
consistent and unchanging model of the world.
But in many problem domains, it is not possible to create such
m
Himanshi
Assistant Professor, LPU
Outline
Generate-and-test
Hill climbing
Best-first search
Problem reduction
Constraint satisfaction
2
Generate-and-Test
Algorithm
1. Generate a possible solution.
2. Test to see if this is actually a solution.
3. Quit if
Natural Language Processing
Chapter 15: Rich & knight
NLP Intro
Language is meant for Communicating about the world.
By studying language, we can come to understand more about the world.
If we can succeed at building computational mode of language, we wil
BYRAHUL
B.T/M.T(B1702)
INTRODUCTION
AI programs that achieve expert level competence in solving
problems in particular task area by use of knowledge base
about that particular task area are known as KNOWLEDGE
BASED OR EXPERT SYSTEMS.
These are complex AI
Expert System Architecture
Structure
The internal structure of an expert system can
be considered to consist of three parts:
The knowledge base
The database
The rule interpreter
This is analogous to the production system
where we have the set of prod
Product Models and Metrics
Product Models and Metrics
There are a large number of product types: requirements documents, specifications, design, code, specific components, test plans, . There are many abstractions of these products that depend on differen