A.I. Final Assignment Submitted by: M. Rehan Asghar BSSE 6 - 15126

Submitted to: Miss Amina Khan 3/7/17 Department of CS & IT

A.I. Final Assignment

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A.I. ASSIGNMENT

Question no 1: Differentiate between the followings:

Uninformed and Informed Search:

An Un Informed (a.k.a. blind, brute-

force) search algorithm generates the

search tree without using any domain

specific knowledge. The two basic

approaches differ as to whether you check

for a goal when a node is generated or when

it is expanded.

Examples of Uninformed Search are:

• Breadth First Search

• Depth First Search

• Depth Limited Search

• Depth First Iterative Deepening

An Informed search tries to

reduce the amount of search that must

be done by making intelligent choices

for the nodes that are selected for

expansion. This implies the existence of

some way of evaluating the likely hood

that a given node is on the solution

path. In general this is done using

a heuristic function.

Examples of Uninformed Search are:

• A * Search

• Admissible Heuristics

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Question no 1: Differentiate between the followings:

Blind and Heuristics Search:

A blind search (also called an uninformed search) is a search that has no

information about its domain. The only thing that a blind search can do is

distinguish a non-goal state from a goal state.

For example: Breadth and Depth First Searches

In Artificial Intelligence and mathematical optimization, a heuristic is a

technique designed for solving a problem more quickly when classic methods

are too slow, or for finding an approximate solution when classic methods fail

to find any exact solution. This is achieved by trading optimality,

completeness, accuracy, or precision for speed. In a way, it can be considered a

shortcut.

A heuristic function, also called simply a heuristic, is a function that

ranks alternatives in search algorithms at each branching step based on

available information to decide which branch to follow.

For Example: A * Search etc.

Q2: Suppose you have to implement a voice enabled interface for

your laptop. What problems could you face while developing the

software?

Ans: If I have to implement a voice enabled interface for my laptop, then

there could be the number of problems in the implementation depending

upon the conditions, functionalities and atmosphere.

Some of the possible problems could be like following:

1. First, my voice should be recognized well.

2. My voices accent should be understandable for the interface.

3. I have to design a virtual voice interface so that it could understand the

common language and words.

4. It should not confuse if the communication left uncompleted.

5. It should be able to understand whether the said word means to

interpret as a word or a call to do something.

A.I. Final Assignment

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6. It should be able to interpret as many words and commands as it could

do.

7. One challenge is if we increases the domain of the voice enabled

interface then the difficulties will increase directly proportional to it.

8. As our system will rely on the context and the conversations by us, it

should be able to interpret the functionalities well.

9. If a word said is not recognizable by the system, then it should not crash

or call the wrong functionality but it should ask for repeat or should

stop.

These and many more could be the challenges in the implementation of

a voice enabled interface.

Q3: This question is related to your term project. What if you have

to convert your project into a computer vision based project? Which

module will you choose to change and why?

Ans: Our term project was to

develop a spying car like robot

with camera so that we can send

live feedback, take photos and

videos of the surroundings.

If I have to convert my

project into a computer vision

based project then I will try to

change the program of the robot.

I would like to use an algorithm

that my robot could learn about its surroundings rather than just being

controlled by the Bluetooth remote controller.

I would like to use feedback neural network algorithm so that it could learn

about things and remind them. If it could recognize things wrong then it cold

be able to send it as a feedback and learn it so next time it recognizes it

correctly.