CSE 471/598 Homework, Projects, and Exams
Notes: (1) Homework's and projects should be submitted before 4:00pm
on the due date.
To make it more convenient to you, the deadline is further extended to
Tues. instead of Mon.;
penalty applies at 2 (absolute) points a day. Tip: don't be late as you're
other courses too.
have a choice of doing 4 sets (7.5 points each) or 5 sets (6 points each)
As we agreed in the classroom, the last set is optional if you choose to
do 4 sets
of homework. You can make your decision on the last due date.
(4) You can
submit your homework to the instructor in class or to TA: Mr. Dasari,
Your suggestions are welcome. Please share your view with me.
HW1: (Problem Solving) Ex 1.7, 2.4, 2.10, 3.3, 3.4
Deadline: Feb. 4 (Fri.), 2000.
HW2: (Knowledge and Reasoning) Ex 6.7, 6.12, 7.2 (a, b, c, d),
7.11 (a, b, c, d) , 9.4, 9.5 (a, b)
Deadline: Mar 7 (Tues.), 2000.
HW3: (Learning) Ex 18.3, 18.3 extended (create a decision tree about
the move-forward for the wumpus world, and propose how you can make a learning
agent for this world - it's related to the second project), 18.5, 18.7
Deadline: Mar 24 (Fri.), 2000 during the class.
HW4: (Acting Logically) Ex 11.2 (a) and (b), 11.4 (Hint: without POP,
can you do that? If you can't, why can't? You are actually discovering
the anomaly!), 13.2 (The Wumpus World only)
Deadline: Apr 18 (Tues.), 2000.
HW5: (Uncertain Knowledge and Reasoning) Ex. 14.1 (Hint: The first principles
are the definition of conditional probability), 14.6, 15.1 (a), (b), and
Deadline: May 2 (Tues.), 2000.
P1: (Agent and its environment) 2.5 and 3.17 (4.14b is removed)
Deadline: Mar 20, 2000. Submitted to TA: Mr. Dasari
You need to submit your code with a short
report that includes the following
P2: Create an intelligent agent via Machine Learning (Decision Tree Induction
in the Wumpus world :-)
A brief summary what P1 is
What're your approach and design
How to run it and what is the expected result
Any problem or discussion
Deadline: May 1, 2000. Submitted to the instructor or TA: Mr.
Create an environment for the famous Wumpus world (refer to Pages 154-155,
a grid of 4X4)
Build a random agent (RA) for the task
Design a learning scheme so that data from running RA can be collected
Learn a more intelligent agent (IA) than RA so that it can react appropriately
according to the percepts
How many trials (attempts by RA in order of 10, 100, 1000, 10000)
do you need to learn IA?
Provide a sample of your data (attribute-values) and list the rules learned
from the data
Appropriately reacting is better than randomly reacting. However, can we
learn even more? What kind of knowledge can your learning system can maximally
How does your learning algorithm achieve that? What are the rules (knowledge)?
Analysis and discussion
There will be a quiz of 2 problems on Wednesday, March
22 to help you review the materials we've covered so far (March
8). The quiz is open book and about 10-15 minutes.
Two sessions of the late mid-term will be held on Friday April
14, 2000 and Wednesday April 19, 2000 during class hours in
the classroom. The first session is about Parts I, II, and III, and the
second session is about Parts IV, V, and VI on the topics we have covered
until April 7. It's close book.