Spice Trader AI

Spice Trader AI is a niche game development project focusing on a single-player experience centered around resource trading and AI learning. The core gameplay loop revolves around the player buying and selling 'Spice' (inspired by Dune) in a fluctuating market. The player competes against an AI opponent that initially operates based on predefined rules and heuristics. However, this AI opponent 'learns' and adapts its trading strategies based on the player's transaction history (inspired by the Order Histories Scraper). The AI learning mechanism can be implemented using a simple reinforcement learning algorithm or even a rule-based system that dynamically adjusts rule weights based on observed player behavior and market outcomes. The 'Ex Machina' inspiration comes in the sense that the player is implicitly 'testing' and influencing the AI's development through their gameplay.

Story & Concept: The player is a fledgling Spice trader in a remote outpost. The AI controls a powerful, established trading house. The player's goal is to amass more wealth than the AI by the end of a set period (e.g., 100 game days). The market is affected by random events (e.g., storms, political instability) that create unpredictable price fluctuations. The AI initially trades based on predictable patterns. As the game progresses, it analyzes the player's past trades (quantities, timing, prices) to identify patterns and exploit them, becoming a more formidable opponent. The game ends when either the player or the AI has amassed a predetermined amount of wealth or after the set number of game days has elapsed.

How it Works:
1. Data Collection: The game tracks all player transactions (buy/sell orders, quantities, prices, timestamps). This data is stored internally. No external servers are needed, ensuring low-cost operation.
2. AI Training/Adaptation: After each in-game day (or at set intervals), the AI analyzes the stored transaction data. A simple algorithm (e.g., Q-learning with discretized state and action spaces, or a weighted rule-based system) is used to adjust the AI's trading strategy. For instance, if the player consistently buys Spice in large quantities after a specific market event, the AI might start buying up Spice just before that event to artificially inflate the price.
3. Dynamic Market: The game engine simulates a dynamic market with prices influenced by supply and demand, random events, and the actions of both the player and the AI.
4. Simple UI: The user interface can be kept simple, focusing on displaying market information (price charts, current Spice supply), player inventory, and AI opponent's estimated wealth.

Implementation Details:
- Engine: Unity, Godot, or even a simple Python-based framework (e.g., Pygame) could be used.
- AI: A basic reinforcement learning library (e.g., TensorFlow Lite for simpler deployment, or a custom-built rule-based system).
- Art Style: Minimalist or pixel art to keep development time and costs low.

Earning Potential: The game can be sold on platforms like Itch.io or Steam for a low price (e.g., $5-$10). Its niche appeal (trading simulation with AI learning) can attract a dedicated audience. Post-launch, the game can be expanded with new market events, AI strategies, and trading mechanics through DLC or updates.