ALLAMA IQBAL OPEN UNIVERSITY, ISLAMABAD
Plagiarism or hiring of ghost writer(s) for solving the assignment(s) will debar the
student from award of degree/certificate, if found at any stage.
assignments borrowed or stolen from other(s) as one’s own will be
penalized as defined in “AIOU plagiarism policy”.
Semester: Spring 2011
ASSIGNMENT NO. 1
All questions carry
What is intel
ligence with reference to A.I? E
laborate the various domains
Elaborate the uses and applications of A.I in manufacturing, medicine,
defense and other applied discipline?
Discuss the role of
intelligent agent. Also elaborate requirements of
What are the steps during planning of problems using state space
How does hill climbing ensure greedy local search? What are the
problems of hill
Illustrate the depth first search with the help of a suitable example.
Give an example of a problem for which breadth
first search would work
better than depth
Prove that uniform cost search is a special case
of A* search.
Explain the concept of flow control and recursion. Use Lisp to demonstrate
ASSIGNMENT NO. 2
Total Marks: 100
All questions carry equal marks.
List out the conditions to apply forward chaining. What
are the steps
involved in forward chaining?
Explain unification with the help of an example?
Discuss the role of a planning agent? Also explain the basic
representation for planning.
Explain the working operation of partial order pla
What are the semantic network and how do they perform inheritance?
Give detailed description on their usage.
Illustrate the use of predicate logic to represent the knowledge with
What are the
applications of NLP? Also explain the structure ambiguity
in natural language.
Explain the different methods of learning.
What is an expert system? Explain the structure of an ES.
Robot is kind of ES. Explain the types and characteri
stics of robot
Artificial Intelligence: A Modern Approach by Russel & Norving
Artificial Intelligence and Intelligent Agents
Introduction, Intelligence Defined, Aspects of
Artificial Intelligence as a Discipline, Purpose, Uses and Applications of A.I
in Manufacturing, Medicine, Defense, Chemistry, and other Applied
Disciplines, Tools and Techniques used in A.I, Intelligent Agents, Structure
Unit No. 2
Search Theory, Formulating Problems, Solving Problems, Finding Paths,
Avoiding Repeated States, State Transition Diagram, Constraint
Satisfaction, Depth First, Breadth First, Hill Climbing, Beam Search, Best
Beta Search, A * Search, Branch and Bound, Heuristic
Pruning, Heuristic Continuation and Dynamic Programming Searches.
Unit No. 3
Introduction to Lisp, Defining Programs, Basic Flow of Control, Basic
Debugging, Recursions, The
For Function, Scope of Variables, Local
Variables, Building up List Structure.
Unit No. 4
Logic & Deduction
Logic Defined, Syntax and Semantics, Extensions and Notational
Variations, Using First Order Logic, Logic Agents, Reflex Agent, Goal
nts, Indexing, Retrieval, and Unification, Theorem Provers,
Forward and Backward Chaining, Forward and Backward Chaining
algorithms, Frame Systems and Semantic Networks, Forward
Unit No. 5
Planning Agent, Planning a
nd Problem Solving, Planning in Situation
Calculus, Basic Representation for Planning, Partial Order Planning, Partial
Order Planning Algorithm, Planning with Partially Instantiated Operators,
Knowledge Engineering for Planning,
Unit No. 6
Introduction, Knowledge based System, Inheritance, Prepositional and
Predicate Logic, Constraints, Knowledge Representation Using Rules,
Frames, and Semantic Nets, Approaches to Semantic Nets, Production
Rules, Knowledge Representation and
Databases Nary Relations, Selection,
Projection, Joins, and Problems of Knowledge Representation.
Unit No. 7
Natural Language Processing
Syntax Analysis/Parsing, Semantic Analysis, Problems, Pragmatics,
Morphology, Applications of NLP, Disadvantages of
Bilingual, Multilingual, Structure Ambiguity in Natural Language,
Discourse Understanding, Discourse Boundaries
Structure, Advantages, Applications of Speech Recognition,
Problems of Speech Recognition
Unit No. 8
Introduction, Rote Learning, Learning by Taking Advice, Learning in
Problem Solving, Learning from Examples (Induction), Learning from
Observations, Explanation Based Learning, Learning by Experience,
Introduction, Methods of Lea
rning, Classification of Learning
Strategies, Components of Machine Learning System, Limitation in terms of Speed.
Unit No. 9 Expert Systems (ES)
Nature of Expert Systems, Features and Characteristics of Expert Systems,
Structure of Expert Systems/ Com
ponents, Roles Involved in Building ES,
Difference between Expert Systems and Conventional Computer Programs,
Expert System Applications, Limitations of Expert Systems, Introduction &
Types of Robots, Classifications and Characteristics of Robots.
Students/groups shall be given simple problems at different points to
understand and apply AI techniques learned in particular unit. A teacher
may take a simple problem and carry it over to clarify the concept
throughout the course. Students/groups shall b
e given additional home
problems to practice during open lab at home.