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CIS 475 Fall 2006 Midterm Exam Preparation: Artificial Intelligence and Prolog - Prof. Pet, Exams of Computer Science

Preparation materials for the midterm exam of cis 475 - artificial intelligence course offered at cau in fall 2006. The topics covered include prolog programming, logic and reasoning, pattern matching, list operations, state-space, search algorithms, heuristic search algorithms, and problem composition. Students are expected to understand the concepts, be familiar with search algorithms and heuristics, and be able to define evaluation functions.

Typology: Exams

Pre 2010

Uploaded on 08/04/2009

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CIS 475 - Fall 2006 - Preparation for Midterm Exam
Notes
Visit these topics in the “Notes” section of the class web-site http://www.cis.cau.edu/475.
The topics indicate the chapters in the textbook!
1. Introduction to Artificial Intelligence
2. AI Programming
3. Advanced Prolog Programming
4. Basic Problem-Solving Strategies
5. Informed/Heuristic Search
6. Project: Adventure Games
7. Problem Decomposition and AND/OR Graphs
Key Elements
1. Logic and Reasoning: Define rules in First Order Predicate Logic and translate them into Prolog
rules (see family.pl)
2. Pattern Matching in Prolog: How does Prolog unify variables? Examples, CAU Tally and
Fraction Calculator. Understand how complex data structures can be defined in Prolog, and
how we can match them.
3. List-operations in Prolog: Review the various predicates that we defined to manipulate lists.
Basic concept:
a) define a terminal rule that matches with an empty list or a list with one element;
b) define a recursive rule that separates the list in head and tail, and calls to solve the problem
for the tail.
4. State-space: a problem can be defined in form a state-space; the four components are:
a) the set of states,
b) the set of allowed transitions between states,
c) the set of start states, which is a subset of the set of states, and
d) the goal-definition, which also represents a subset of the set of states.
/home/molnar/Doc/Classes/CIS475/F06/midterm-prep.odt 10/11/2006 1 of 2
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CIS 475 - Fall 2006 - Preparation for Midterm Exam

Notes

Visit these topics in the “Notes” section of the class webs ite http://www.cis.cau.edu/475. The topics indicate the chapters in the textbook!

  1. Introduction to Artificial Intelligence
  2. AI Programming
  3. Advanced Prolog Programming
  4. Basic ProblemS olving Strategies
  5. Informed/Heuristic Search
  6. Project: Adventure Games
  7. Problem Decomposition and AND/OR Graphs

Key Elements

  1. Logic and Reasoning: Define rules in First Order Predicate Logic and translate them into Prolog rules (see family.pl)
  2. Pattern Matching in Prolog: How does Prolog unify variables? Examples, CAU Tally and Fraction Calculator. Understand how complex data structures can be defined in Prolog, and how we can match them.
  3. Listope rations in Prolog: Review the various predicates that we defined to manipulate lists. Basic concept: a) define a terminal rule that matches with an empty list or a list with one element; b) define a recursive rule that separates the list in head and tail, and calls to solve the problem for the tail.
  4. States pace: a problem can be defined in form a states pace; the four components are: a) the set of states, b) the set of allowed transitions between states, c) the set of start states, which is a subset of the set of states, and d) the goalde finition, which also represents a subset of the set of states. /home/molnar/Doc/Classes/CIS475/F06/midterm prep.odt 10/11/2006 1 of 2
  1. Search Algorithms: how do the basic search algorithms work? How do they differ in performance? What has to be considered when choosing a search algorithm? Be familiar with terms like branching factor, length of the solution path, search direction, completeness, optimality.
  2. Heuristic Search Algorithms: using additional information about the problem to expedite the search. A heuristic evaluation function provides an estimate of how promising a node would be in the quest for the goal. Be able to discuss the differences between the various heuristic search algorithms; define a heuristic evaluation function for a given problem.
  3. Problem Composition: An alternative approach to the search space: nodes are subproblems. The search algorithms can be used in a similar way. The solution in the state space is path that includes all the states that have to be visited, in the AND/OR graph, the solution is an AND graph including all the subproblems that have to be found.

Logistics

● Date: Friday, October 13, 2006 at 1 pm ● Location: CMWARE 210 ● Bring pen or pencil, paper will be provided. ● NO BOOKS, NO NOTES, NO CALCULATOR, NO COMPUTER ● ALLOWED: one “cheats heet”: single sheet of paper, letter size, double sided. ● Review Session: Thursday, October 12, 2006 at 3:30 pm in SRB 2037. /home/molnar/Doc/Classes/CIS475/F06/midterm prep.odt 10/11/2006 2 of 2