1. Guess a random word with n errors
The Hang Man Solver
Guess a random word with n errors

2. The problem A number of wrong guesses is selected.
The computer picks a word randomly from a word bank
The player sees the length of the word.
The player guesses letters in order to guess the entire word
When correct, meaning the letter is in the word, the player continues
After n wrong guesses , meaning guesses in which the letter is not in the word, the game ends.

3. The problem - difficulties
New word at each round – Relevancy of history?
Error bound
Unknown action result
Unknown game words & probability of letters
Many possible actions
Huge state space

4. Solution – Modeling Guess DB Attributes Goal attribute - Win
Decision Trees
QLearner
Guess DB
Based on previous games
Attributes
Letters
Word length
Win ?
Goal attribute - Win
State space definition:
Word length
Letters in
Letters out

5. Solution – Why Simple data set creation Learning from game results
Decision Trees
QLearner
Simple data set creation
Learning from game results
Can handle many attributes
Learning from game results
The problem is a MDP
Assigning q-value without probability knowledge

6. Results Over 50% success for both methods
Q-learner reached higher results – up to 80% success
Probably due to bounded computation resources
Benchmarks
Random guess
One letter natural distribution
Majority

7. Results - QLearner

8. Results – Tree Search

9. Results – Tree Search

10. Thank You!