gameforged 0.1.1

A comprehensive Python framework for game theory modeling, analysis, and simulation.

GameForge

A comprehensive, modular framework for advanced game theory applications, integrating classical, computational, behavioral, and AI-driven game theory into a unified, scalable ecosystem.

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Overview

GameForge is a powerful, extensible library designed to facilitate game theory research, simulation, and application across diverse domains. Whether you are a researcher, developer, or strategist, GameForge provides tools to model, analyze, and refine strategic interactions using a wide range of theoretical and computational approaches.

GameForge supports:

• Classical Game Theory – Nash equilibria, mixed strategies, extensive and strategic forms.
• Computational Game Theory – Algorithmic analysis, AI-driven game strategies, and equilibrium computation.
• Behavioral Game Theory – Human decision-making biases, prospect theory, and bounded rationality.
• Multi-Agent Systems & AI – Reinforcement learning, adaptive strategies, and agent-based modeling.
• Metagaming & Dynamic Environments – Iterated play, evolving incentives, and external factors.

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Features

1. Game Representation & Modeling

• Extensive Form (game trees, sequential decisions, perfect/imperfect information)
• Strategic Form (payoff matrices, simultaneous play)
• Graph-Based & Hybrid Representations

2. Computational Analysis

• Equilibrium Computation (Nash, correlated, evolutionary)
• Algorithmic Strategy Optimization
• Monte Carlo & Minimax Simulations

3. Behavioral & Psychological Modeling

• Prospect Theory & Risk Preferences
• Social Preferences & Fairness
• Framing Effects & Decision Heuristics

4. Multi-Agent Systems & AI Integration

• Reinforcement Learning Agents
• Adaptive Strategy Learning
• Agent-Based Modeling for Dynamic Environments

5. Game Length & Complexity Refinements

• Finite vs. Infinite Horizon Adjustments
• Endgame Scenarios & Tipping Points
• Computational Complexity & Algorithmic Playability

6. Metagaming & External Incentives

• Iterated Play & Reputation Systems
• Policy & Regulatory Game Theory
• Real-World Incentive Modeling

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Installation

GameForge is in active development. Once released, it will be available via PyPI:

pip install gameforge