Game Trainer
Tic-Tac-Toe
Connect Four
Gomoku
Undo
New game
Setup
X plays
Human
Computer
O plays
Human
Computer
Engine (trainer & computer)
Minimax · α-β
Monte Carlo Tree Search
Search depth
plies (half-moves) the engine looks ahead
Simulations
random games played per decision
Exploration constant c
low = focus on best moves, high = try everything
Smart rollouts
(simulated players take wins and block losses)
Heatmap on board
Analyse my moves
Game review
Each move is graded against the trainer's analysis of the position it was played in.
Trainer
Insight
Search tree
Convergence
How it decides