1. Isolation – Champion Program
COMS W4701 Project 3
Spring 2011
Isolation – Champion Program
Albert Jimenez (alj2110)

2. Board Representation Graph Representation Boolean 2D Array
Each node is a free block
Gets smaller as the game progresses
Boolean 2D Array
Simpler
3 – 5 times faster when generating new boards 1

3. Alpha Beta Generating and Ordering New Boards Evaluation Function
Statistical analysis
Correlation between distance of players of chosen board and whether the players are directly reachable.
Exploited correlation to achieve more pruning
Evaluation Function
Early in the game it is not clear who is losing/winning
Eval(board) = currentPlayer.numMoves – opponent.numMoves
Ensures more freedom to apply other strategies
Reduces the chances of the opponent trapping you O X

4. Main Strategy: Achieving Isolation
Detecting Isolation
Determine if players are separated after generating new boards
If so, this is a terminal node and the second evaluation function can be applied
Can immediately determine if board is likely to be a win/loss without going any deeper
Evaluation Function 2
Compute number of blocks reachable from both players
Compute difference in reachable blocks = ‘diffReachable’
Positive value means a likely win
Negative value means a likely loss
Eval2(board) = (diffReachable > 0) ? INFINITY + diffReachable : -INFINITY + diffReachable
Distinguishes between ‘good’ or ’bad’ win/loss O X

5. Main Strategy: During Isolation
Alpha Beta becomes Obsolete
It is unnecessary to care about what move the other player might take
By focusing on only one’s own moves, can reach twice the depth
Computing Optimal Isolation Path
Recursive approach to choose the longest path
Heuristics were used to prune bad moves (moves that decrease number of reachable blocks) O X