We introduce a new sub-symbolic Artificial Chemistry, called the Meta-Atom Artificial Chemistry. It treats composite particles (composites of random boolean networks, RBN) as a new type of higher level atom, a meta-atom . These complex structures, together with a new kind of link, then form even larger, multi-level, structures. We show that Meta-Atom Artificial Chemistry exhibits rich behaviour, including reaction pathways that resemble catalytic reactions.

Our MetaChem framework supports the definition and combination of artificial chemistries. Here we describe an implementation of MetaChem in an object oriented language. We briefly define MetaChem, and provide an example in the form of a toy AChem: StringCatChem. We present the class hierarchy used to define MetaChem such that the implementation can run directly from a graph description of some AChem. This matches the description given by the formal framework definition. We also describe some generic functions of MetaChem that have been implemented and used in StringCatChem. This implementation is available on GitHub.

We introduce a modularisation of artificial chemistries (AChems). This allows us to define a standard linking method between AChems. We illustrate the approach with a system that nests a Jordan Algebra AChem (JA AChem) inside agents of SwarmChem, and show how our modular approach allows us to define and experiment with multiple variants in a standard manner. Potential for future formalisation is discussed.

Natural chemistry deals with non-deterministic processes, and this is reflected in some artificial chemistries. We can tune these artificial systems by manipulating the functions that define their probabilistic processes. In this work we consider different probabilistic functions for particle linking, applied to our Jordan Algebra Artificial Chemistry. We use five base functions and their variations to investigate the possible behaviours of the system, and try to connect those behaviours to different traits of the functions. We find that, while some correlations can be seen, there are unexpected behaviours that we cannot account for in our current analysis. While we can set and manipulate the probabilities in our system, it is still complex and still displays emergent behaviour that we can not fully control.

We explore the effects that different reactor types have on Spiky-RBN AChem systems, looking at mass conserving and flow reactors. To assist in analysing the behaviour we introduce an activity measure based on possible system state changes as a result of changes in particle properties. This leads to a discussion on approaches to engineering complex systems towards specific goals.

We present a subsymbolic Artificial Chemistry (ssAChem) in which all properties relevant to bonding are emergent from the underlying dynamical system (an RBN). We explore this ssAChem by evolving a seed set of atomic particles and showing the type of composite particles the system can produce.

We identify some desired mathematical properties of bonds in an Artificial Chemistry (AChem) that promote complexity and open-ended behaviour (i.e. an AChem not designed to display particular behaviours). We identify the underlying structures created by different properties of mathematical products. We use these to exploit existing algebra to generate a potentially open-ended subsymbolic Achem (ssAChem). We give examples of how our approach leads to interesting behaviour, focused on the structure of composite particles within our system.