The MeTTa Programming Language – A meta-programming language built to support self-modifying AI systems, enabling expressive, flexible, and efficient AGI development by allowing AI agents to reason, adapt, and optimize their own code dynamically.
MeTTa programs organically combine elements of functional, logical and probabilistic programming providing a synergetic framework for representing declarative and procedural knowledge.
Each MeTTa program is represented as a subgraph of an Atomspace metagraph, and operates centrally by querying and rewriting portions of Atomspaces.
MeTTa handles highly abstract constructs like run-time self-modifying code simply and naturally. Programs are fully self-reflective – we can read/modify the code inside the programs.
Type system is one of the most important features in terms of application of MeTTa language. Built-in mathematical reasoning by supporting a state-of-the-art type system.
With its open architecture MeTTa embraces very different AI strategies and is intended both for humans to script portions of AGI cognitive processes, and for the programming activity of AGI-related learning and reasoning algorithms themselves.
MeTTa forms the ‘universal translator’ that enables a wide range of AI systems to dynamically collaborate by the creation of compatible Domain Specific Languages within one framework.
MeTTa is the language of the cognitive architecture of OpenCog Hyperon. It functions as the firmware of the wildly variating components that Hyperon is made of and it is the glue that holds everything together.
Cognitive synergy is a core principle in OpenCog Hyperon’s approach to AGI. It refers to the idea that different cognitive processes work together in a mutually beneficial way, enhancing the system’s overall intelligence. Hyperon’s architecture is designed to facilitate this synergy by enabling various AI modules, such as PLN (Probabilistic Logic Networks) and ECAN (Economic Attention Networks), to interact and share information. This synergistic approach allows the system to tackle complex problems by leveraging the strengths of different AI methods.
MeTTa emerges as the ideal language for AGI due to its robust framework that goes beyond traditional programming capabilities. Its declarative and functional approach allows for the sophisticated knowledge representation and reasoning AGI developers require, making it possible to handle complex relationships and data structures. The integration with the Distributed Atomspace (DAS) enhances its suitability for AI applications by providing a versatile knowledge database.
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