The MASTERMIND system is a sophisticated component of the broader AI infrastructure, designed to serve as an agency control structure with advanced reasoning capabilities. Here’s a detailed overview of its functionalities and role within an AI framework: System Coordination and Workflow Management: MASTERMIND orchestrates interactions between various components within an AI system, managing the overall workflow and ensuring that all parts function cohesively. It initializes the system, sets up the environment, and coordinates data processing […]

The LogicTables class in logic.py is designed to handle logical expressions, evaluate their truth values, and manage beliefs as valid truths. It integrates with the SimpleMInd or similar neural network system to process and use truths effectively. Key Features: Initialization and Logging The LogicTables class initializes with logging configuration to capture debug information: Adding Variables and Expressions Truth tables are generated to evaluate logical expressions: Expressions are evaluated using logical operators: def evaluate_expression(self, expr, values):allowed_operators […]

core choice logging and self-improvement readiness Current state To show that mindX is or is not a Gödel machine, we need a single, accurate log of core choices: what was perceived, what options were considered, what was chosen, why, and (when available) outcome. 1. Gödel choice schema and global log 2. Instrument core decision points 3. Ollama-driven self-improvement readiness 4. API and UI (optional) 5. File and dependency summary Area File(s) Change Core directive docs/survive.md […]