Adversarial Game-Theoretic Framework

A Adversarial Game-Theoretic Framework is a game theory framework that models competitive interactions between rational agents with opposing objectives in strategic environments.

• AKA: Competitive Game Framework, Game Theory Framework, Zero-Sum Framework, Strategic Competition Framework.
• Context:
  • It can typically model Zero-Sum Interactions where one agent's gain equals another's loss.
  • It can typically compute Nash Equilibrium for optimal strategy profiles in competitive scenarios.
  • It can typically apply Minimax Algorithms to determine worst-case optimal decisions.
  • It can typically analyze Mixed Strategy involving probability distributions over pure strategys.
  • It can typically evaluate Payoff Matrixes representing outcome values for strategy combinations.
  • It can often incorporate Incomplete Information through Bayesian games and belief updates.
  • It can often extend to Multi-Agent Settings with coalition formation and alliance dynamics.
  • It can often model Sequential Decisions through extensive form games and game trees.
  • It can range from being a Two-Player Framework to being a Multi-Player Framework, depending on its participant count.
  • It can range from being a Perfect Information Framework to being an Imperfect Information Framework, depending on its knowledge structure.
  • It can range from being a Zero-Sum Framework to being a General-Sum Framework, depending on its payoff structure.
  • It can range from being a Static Framework to being a Dynamic Framework, depending on its temporal structure.
  • ...
• Example(s):
  • Classical Game-Theoretic Frameworks, such as:
    • Prisoner's Dilemma Framework for cooperation versus defection.
    • Rock-Paper-Scissors Framework for cyclic dominance.
    • Matching Pennies Framework for pure conflict.
  • Video Game Application Frameworks, such as:
    • RTS Game-Theoretic Framework for resource allocation strategy.
    • Fighting Game Framework for yomi layers and mix-up theory.
    • MOBA Draft Framework for pick-ban optimization.
  • AI Competition Frameworks, such as:
    • AlphaGo Framework for Monte Carlo tree search with neural network evaluation.
    • OpenAI Five Framework for multi-agent reinforcement learning.
    • Libratus Framework for imperfect information game solving.
  • Economic Game Frameworks, such as:
    • Auction Theory Framework for bidding strategy.
    • Market Competition Framework for pricing decisions.
  • ...
• Counter-Example(s):
  • Cooperative Game Theory Framework, which models mutual benefit rather than opposition.
  • Decision Theory Framework, which handles single-agent decisions without strategic interaction.
  • Optimization Framework, which seeks objective maximization without adversarial consideration.
• See: Game Theory Academic Discipline, Zero-Sum Game, Nash Equilibrium, Adversarial Video Game Pattern, Video Game Adversarial Strategy, Video Game AI Opponent, Minimax Decision Rule, Mixed Strategy Nash Equilibrium, Competitive Video Game System, Video Game Counter-Strategy System.

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