G.O.D Framework

Introduction

The ai_universal_truths.py script provides a system for managing, reasoning over, and querying universal truths, constants, and ontologies. It serves as a core knowledge base component for the G.O.D Framework, facilitating decision-making processes, logical inferences, and AI ontological reasoning tasks.

Purpose

The script aims to fulfill the following objectives:

• Representing universal truths and constants as structured data, enabling logical and rational operations.
• Providing reasoning mechanisms for AI to interpret and derive insights from knowledge trees.
• Facilitating querying and fetching of universal constants for downstream tasks.
• Supporting advanced modular reasoning workflows across various AI systems, from predictive analytics to anomaly detection.

Key Features

• Ontology Management: Maps defined concepts and entities into knowledge structures for logical inferences.
• Knowledge Querying: Efficient querying for constants, rules, and relations.
• Reasoning Capabilities: Allows logical deductions and automated derivation of relationships.
• Integration Ready: Seamlessly integrates with other reasoning and inference modules like ai_infinite_consciousness.py.
• Self-Updating: Dynamically updates or extends universal truths when new data pipelines add verified knowledge.

Logic and Implementation

Below is an example implementation outline showcasing how universal truths are stored, queried, and reasoned upon:

class UniversalTruths:
    """
    Core class for managing and querying universal truths in the G.O.D Framework.
    """

    def __init__(self):
        self.truths = {}

    def define_truth(self, name, definition):
        """
        Define a new universal truth.

        Args:
            name (str): Unique identifier for the truth.
            definition (any): The value or logical rule of the truth.
        """
        self.truths[name] = definition
        print(f"[INFO] Truth '{name}' added to the system.")

    def query_truth(self, name):
        """
        Fetch the definition of a defined universal truth.

        Args:
            name (str): The name of the truth to query.

        Returns:
            any: The value or definition of the truth.
        """
        if name in self.truths:
            return self.truths[name]
        else:
            raise KeyError(f"Truth '{name}' not found.")

    def reason_over_facts(self, rules):
        """
        Perform reasoning operations based on provided logical rules.

        Args:
            rules (list): List of lambda functions or logical operators.

        Returns:
            bool: The outcome of the reasoning operation.
        """
        try:
            results = [rule(self.truths) for rule in rules]
            return all(results)
        except Exception as e:
            print(f"[ERROR] Reasoning failed: {e}")
            return False

# Example Usage
if __name__ == "__main__":
    ut = UniversalTruths()
    # Define truths
    ut.define_truth("gravity_exists", True)
    ut.define_truth("speed_of_light", "299,792,458 m/s")

    # Query truths
    print(ut.query_truth("gravity_exists"))  # Output: True

    # Reasoning over truths
    rules = [
        lambda truths: truths["gravity_exists"] is True,
        lambda truths: "speed_of_light" in truths
    ]
    print(ut.reason_over_facts(rules))  # Logical outcome: True
        

Dependencies

This script is self-contained but integrates smoothly with other modules. It has no core external dependencies.

Integration with the G.O.D Framework

The ai_universal_truths.py script ties in with other components of the G.O.D Framework:

• ai_infinite_consciousness.py: Acts as an information provider and ontological backbone.
• ai_explainability.py: Explains decisions and inferences derived from universal truths.
• ai_model_validation.py: Validates models based on grounded universal truths.

Future Enhancements

• Integration with external semantic libraries like OWL and knowledge graph systems (e.g., Neo4j).
• Support for probabilistic truths and Bayesian reasoning.
• An API for broader knowledge access and external system interaction, including cloud-aware integrations.