Some CS-4701 Projects Ideas
- Character Recognition using Neural Nets
- Backgammon
- Strategic Influence in Go
- BlackJack
- 3-D-Tic-Tac-Toe
- Edge-detection using Neural Nets
- Implementing Virtual Predators in a Virtual Environment
- Using Neural Networks to Forecast Dow Jones Industrial Average
- Learning to Play Checkers
- Build a system that plays Hearts in which each ``player'' uses a
different strategy. E.g.,
One player uses a random strategy, one uses a set of hand-coded rules, and the
others use heuristic methods with different static evaluation functions.
- Apply a genetic algorithm to the problem of automatic generation
of computer programs.
- Write a program to identify English characters from bitmaps.
Various features are extracted from the bitmap, such as the Euler number
(measure of how many holes in an object), centroid, and diretional tendency.
Then the 26 possible characters are ranked, under a rule that measure
similarity of the observed features to features of canonical training
examples.
- Apply a genetic algorithm to the problem of learning natural
language grammars.
- Build a system that uses heuristic search (with minimax and
alpha-beta pruning) to play Connect-4. Evaluate it against human players.
- Build a generic rule-based system for some domain and compare
the effectiveness of forward and backward reasoning.
- Build (and train) a system that plays Connect-4 using a neural
network.
- A chess endgame player. An interesting variant is to design
a method that learns end-game rules from examples and compare it with
hand-generated chess endgame players.
- Build a suite of neural network algorithms; test them on
selected datasets from the machine learning dataset archive; determine why
they did or did not work.
- A computer bidding system for the game of bridge. Bridge, unlike
chess, is a game of incomplete information, which makes standard game-tree
search techniques unusable.
- A theorem-proving system for some (small) subset of mathematics.
- A program that generates automatic crossword puzzles, starting
from a dictionary and an empty board.
- Recreate from its specifications the reinforcement learning
(neural net) system (Tesauro, 1992) that learns to play backgammon by playing
games against itself.
- A reactive, rule-based system that plays tetris.
- Re-implement Samuel's checkers playing program.