lngb
commented
4 hours ago Improvements already included in the version 0.2 from the improvement list :
- Additional game modes.
- Customization (partial)
- Visual and audio feedback
Extra :
- Performed a code cleaning and optimization.
- Included settings function
Possible future expansions:
1. Additional game modes.
Player vs. Player (PvP): Allow two players to play on the same device. Add an option in the menu to choose between PvP or player vs CPU. CPU difficulty levels: Easy: CPU plays randomly. Medium: Implements some basic strategies (blocking or trying to win). Hard: Uses a Minimax algorithm for almost unbeatable behavior.
2. Customization
Symbol Choice: Allow players to choose symbols other than “X” and “O”. Scoreboard Theme: Offer different visual styles for the scoreboard (minimal, ASCII, ANSI colors). Custom size: Implement a larger grid (e.g., 4x4 or 5x5), with different win conditions (e.g., lining up 4 symbols).
3. Statistics and progress.
Wins/Losses/Playoffs Counter: Shows a summary of the player's achievements. Leaderboard: If you implement online or local PvP, records scores in a leaderboard. Match history: Shows the final scoreboards of the last matches.
4. Visual and audio feedback
Dynamic messages: Add motivational messages or jokes depending on player or CPU moves. Sound effects: Use libraries such as pygame or playsound to add: Sounds for moves. Sound effects for winning/losing. Animations: For example, flash the winning line on the grid.
5. Advanced Modes.
Tournament Mode: Create a mode in which the player must win a certain number of games against CPU with increasing difficulty. “Stopwatch” mode: Limit the time for each move (both for the player and the CPU). Puzzle Mode: Provide predefined situations that the player must solve with one move.
6. Online Multiplayer.
Real-time challenges: Use a library such as socket or frameworks such as Flask or Django to implement online matches. In-game chat: Allow players to communicate during the game.
7. Improved artificial intelligence
Implements the Minimax algorithm (or a simplified version) for strategic and intelligent CPU. Use a library such as numpy to make grid management more efficient.