# CSCE 883: Test 3

## Name:___________________________________________________

Show your work for every question but make clear which one is the
final answer by drawing a box around it. Remember to copy the
question number to your answer booklet. In all questions it is
critical that you **show your work**.

**[15 points]** Use sequential covering with the
learn-one-rule to learn a set of rules that can predict the
isBird concept from the examples below. Assume an entropy
threshold of 0.
Example # |
hasBeak |
laysEggs |
hasFeathers |
isBird |

1 |
T |
T |
T |
T |

2 |
T |
T |
F |
T |

3 |
T |
F |
F |
F |

4 |
T |
T |
T |
T |

5 |
T |
F |
T |
F |

**[10 points]**
Given the set of predicates: Father(x,y), ChildOf(x,y),
Niece(x,y), what are the possible specializations (as
defined by FOIL) of the rule:

Niece(x,y) ← ChildOf(x,z)
**[15 points]**
Use inverse resolution to determine what else one would need
to know in order to deduce that

Screams(x) ∧ Runs(Bob) ∧ Giggles(x)

given that,

Tickles(x,y) ∧ Screams(x) ∧ Runs(y).
**[15 points]**
Given the domain knowledge:
- KickPower(Times(10,x)) ← Stamina(x)
- KickDistance(Times(x,cos(y))) ← KickPower(x) ∧ BallAngle(y) ∧ BallDistance(z) ∧ LessThan(z,1)
- CanScore ← DistanceToGoal(x) ∧ KickDistance(y) ∧ LessThan(x,y)

and the positive example (for the CanScore target concept)
- BallAngle(0) ∧ BallDistance(.5) ∧ DistanceToGoal(8) ∧ Stamina(1)

you were able to use the domain knowledge to deduce that
CanScore is true. What is the weakest pre-image of that
deduction?
**[10 points]**
You decide to learn the concept "is in simplest form" over
the domain of algebraic equations. That is, given an
algebraic equation your program has to decide whether or not
the equation is in its simplest possible form. How would you
use EBL to solve this problem?
**[10 points]**
You implement the KBANN algorithm with a domain theory that
has one incorrect statement in it. What happens when you run
the algorithm on a set of examples that contradict the
domain theory. The examples are all correct.
**[10 points]**
FOCL is an extension of FOIL. Can the added functionality in
FOCL guide the hypothesis-space search in a completely wrong
direction? Explain.
**[15 points]**
You have a robot that lives in a 3 by 3 grid world and can
move N,S,E,W by one space. Each time the robot moves he
loses 2 tokes but can pick up tokens from the the space it
reaches. The tokens can be picked up only once. The initial
world looks like:
where R is the robot and the numbers reflect the
number of tokens initially in each space. The goal is to end
up with as many tokens as possible in the least amount of
time. Explain how you would solve this problem with
Q-learning and display the first 5 steps of the Q table.

Jose M. Vidal