A framework and Language for Complex Adaptive System modeling and simulation

Complex adaptive systems (CAS) exhibit properties beyond complex systems such as self-organization, adaptability and modularity. Designing models of CAS is typically a non-trivial task as many components are made up of sub-components and rely on a large number of complex interactions. Studying features of these models also requires specific work for each system. Moreover, running these models as simulations with a large number of entities requires a large amount of processing power. We propose a language, Complex Adaptive Systems Language (CASL), and a framework to handle these issues. In particular, an extension to CASL that introduces the concept of ‘semantic grouping’ allows for large scale simulations to execute on relatively modest hardware. A component of our framework, the observation module, aims to provide an extensible and expandable set of metrics to study key features of CAS such as aggregation, adaptability, and modularity, while also allowing for more domain-specific techniques.