A Masters Project R & D on A YU-GI-OH-inspired turn-based card game featuring advanced AI-driven gameplay. utilizing a deck of cards to summon creatures, cast spells, and traps. The game will showcase sophisticated AI opponents using algorithms like Alpha-beta pruning, Monte Carlo methods, and Reinforcement Learning to make informed decisions.
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Card Decks:
- Each player has a deck of 10-20 cards.
- Cards are divided into three types: Monsters, Spells, and Traps.
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Turns:
- Players take turns drawing cards, playing cards, and executing strategies.
- Each turn has phases: Draw Phase, Main Phase, Battle Phase, and End Phase.
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Battles:
- Players can summon monsters to attack or defend.
- Spells and traps can be used for strategic advantages.
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Winning Conditions:
- Reduce opponent’s life points to zero.
- Alternative win conditions through specific card effects.
AI Mechanics
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Decision Making:
- Implement AI algorithms (Alpha-beta pruning, Monte Carlo, Genetic Algorithms, Reinforcement Learning) for opponent decision-making.
- AI uses past battle data to make better future decisions.
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Adaptive Strategies:
- AI adapts its strategy based on player behavior and game state.
- Dynamic difficulty adjustment to keep the game challenging.
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A fully functional YU-GI-OH-inspired game:
- Enhanced AI and engaging gameplay mechanics.
- 1v1 and potential 5v5 battle modes with animations.
- AI using past battle history for decision-making.
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Unreal Engine 5 Template/Plugin:
- Simplifying the development of similar games.
- Focuses on AI and gameplay (GAS) programming.