System Language
System Language (SL) Foundation
This page explains the System Language concept that inspired BERT's development and provides its theoretical grounding.
The Vision for System Language
As described in Chapter 4 of Systems Science: Theory, Analysis, Modeling, and Design, Mobus proposes developing an "explicit system language to take systemese public" - a formal language that is both machine and human readable for communicating system descriptions.
The Need for a Formal Systems Language
Traditional modeling languages often fall short when representing complex systems:
Many focus on static structure but miss dynamic relationships
Some capture flows but not hierarchical decomposition
Others lack the rigor needed for computational validation
Most don't address the unique properties of adaptive systems
System Language aims to address these gaps, creating a unified approach based on the "systemese hypothesis" - that human thought is fundamentally structured around system concepts.
SL Components and Grammar
Lexical Elements
Primitive ontological elements (boundaries, flows, processes)
Section 4.3
Verbal Descriptions
Structured statements mapping to system relations
Fig. 4.2
Visual Icons
Graphical representations of system elements
Fig. 4.13
Component Tables
Structured descriptions with predefined types
Table 4.1
BERT's Implementation of SL Concepts
Visual Grammar
Icons and graphical elements for system components
Hierarchical Structure
Recursive decomposition matching SL's formal definition
Boundary Definitions
Explicit system boundaries and interfaces
Flow Specification
Typed flows (matter, energy, information) with parameters
Note: BERT represents an accessible implementation of SL concepts to inspire and attract support for formal language specification. The full formal SL specification remains under development.
Computational Properties
System Language's design enables computational analysis through:
Mathematical Foundations - Formal set-theoretic definitions enable rigorous analysis
Machine Readability - Structured format allows automated processing and validation
Simulation Support - Clear semantics enable dynamic system simulation
Verification Capabilities - Formal structure permits consistency checking
BERT demonstrates these capabilities through its complexity calculator, save/load functionality, and structured JSON format.
Additional Resources
Key References
For deeper understanding of the theoretical foundations:
Mobus, G. (2022). Systems Science: Theory, Analysis, Modeling, and Design - Source for DSA methodology and System Language concepts
Mobus, G. & Kalton, M. (2015). Principles of Systems Science - Foundation for the 7-tuple model and system ontology
BERT GitHub Repository - Latest updates and community discussions
Related Concepts
Deep Systems Analysis (DSA) - The comprehensive methodology BERT implements
Systemese Hypothesis - The theory that human thought is structured around system concepts
7-Tuple Model - The formal mathematical definition of system underlying BERT
Getting Help
Documentation: Browse the complete GitBook documentation
Community: Join discussions on GitHub
Examples: Explore the Model Browser for practical applications
Theoretical Background
BERT implements ideas from George Mobus's work on systems science. After an interdisciplinary career spanning naval engineering, robotics, artificial intelligence, computer science, energy systems modeling, and systems science, Mobus identified key limitations in standard systems modeling frameworks like Stella and UML/SysML.
To address these gaps, he proposed the creation of a new formal "System Language" (SL) grounded in systems science principles. BERT represents a first step toward developing this formal systems language, built specifically for modern systems scientists.
Read more about the various components of SL and how they're implemented in BERT.
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