Historical Examples of Effective Communication
Analysis 1.1
The introduction of The Declaration of Independence contains some of the world's most
oft quoted words. The introduction opens by stating the purpose of the document-to
declare the causes that co
MVC ARCHITECTURE
Model view controller is a software architectural pattern for implementing user interfaces on
computer. It divides a given software application into three interconnected parts, so as to separate
internal representations of information fro
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
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 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 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:
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
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
HillClimbing
It is a variant of generate and test in which the feedback
from the test procedure is used to help the generator decide
which direction to move in the search space.
In a pure generate and test procedure, the test function
responds with only a
Artificial Intelligence
Learning
AI systems cannot be called Intelligent until they are able to learn to do new
things and to adapt to new situations.
Learning in terms of Simon[1983], changes in the system that are adaptive on
the sense that they enable
Puzzles
From XKCD Wiki
Jump to: navigation, search
This is a page for problems/puzzles which appear simple but are fiendishly counterintuitive. Try
to keep a nice balance and add quality puzzles. Perhaps solutions can be discussed on the talk
page. We can
USINGPREDICATELOGIC
INTRODUCTION
Previous chapter much has been illustrated about knowledge and KR
related issues
This chapter , illustrates how knowledge may be represented as symbol
structures that characterize bits of knowledge about objects, concepts,
ArtificialIntelligence
oduction
Grand Challenges in Science and
Technology
scienceandtechnologyarechangingrapidly
understandingthebrain
reasoning,knowledge,creativity
creatingintelligentmachines
isthispossible?
whatarethetechnicalandphilosophicalchalle