The papers and videos presented here explore the limitations of current symbolic and sub-symbolic computing models and demonstrate a novel approach using the General Theory of Information (GTI). The demonstration of the prototype implementations highlight the implementation of GTI-based systems, which incorporate knowledge structures, associative memory, and event-driven interaction history to manage autopoietic (self-regulating) and cognitive workflows. These concepts are described fully in the papers referenced here. These systems are designed to dynamically adapt to changing conditions and user interactions, ensuring stability and efficiency. The concept of the digital genome is introduced, which specifies the functional and non-functional requirements of a system, allowing it to autonomously adapt and maintain stability. Two Applications of this approach are demonstrated in video on demand (VoD) systems and medical knowledge-based digital assistants, showcasing the potential of GTI to revolutionize various domains by creating more resilient and intelligent systems that mimic the cognitive and autopoietic behaviors observed in natural intelligence.
Digital Genome and Self-Regulating Distributed Software Applications with Associative Memory and Event-Driven History
Paper by Rao Mikkilineni, W. Patrick Kelly, and Gideon Crawley, discusses the application of the General Theory of Information to build a self-regulating video on demand distributed software application.
Mikkilineni, R.; Kelly, W.P.; Crawley, G. Digital Genome and Self-Regulating Distributed Software Applications with Associative Memory and Event-Driven History. Computers 2024, 13, 220. https://doi.org/10.3390/computers13090220
This video is referenced in our paper submitted to Computers. The video demonstrates the implementation of associative memory and the event-driven transaction history of a distributed software application with a digital software genome specification discussed in this paper.
From Symbolic and Sub-Symbolic Computing to Super-Symbolic Computing
Abstract: Biological systems have a unique ability inherited through their genome. It allows them to build, operate, and manage a society of cells with complex organizational structures where autonomous components execute specific tasks and collaborate in groups to fulfill systemic goals with shared knowledge. The system receives information from various senses, makes sense of what is being observed, and acts using its experience, while the observations are still in progress. We use the General Theory of Information (GTI) to implement a digital genome, specifying the operational processes that design, deploy, operate, and manage a cloud-agnostic distributed application that is independent of IaaS and PaaS infrastructure, which provides the resources required to execute the software components. The digital genome specifies the functional and non-functional requirements that define the goals and best-practice policies to evolve the system using associative memory and event-driven interaction history to maintain stability and safety while achieving the system’s objectives. We demonstrate a structural machine, cognizing oracles, and knowledge structures derived from GTI used for designing, deploying, operating, and managing a distributed video streaming application with autopoietic selfregulation that maintains structural stability and communication among distributed components with shared knowedge while maintaining expected behaviors dicated by functional requirements.
Digital Genome and Medical Knowledge-Based Digital Assistant
A New Class of Intelligent Machines with Self-Regulating, Even-Driven Process Flows for Designing, Deploying, and Managing Distributed Software Applications by Rao Mikkilineni and Patrick Kelly
Presented at the 11th International Conference on Human Agent Interaction
Autopoietic Machines 