Identifying multi-level emergent behaviours in agent-based simulations using Complex Event Type specifications

Agent-based simulations (ABS) are used in many domains to study complex systems. These are systems where non-linear effects can result from these emergent behaviours, making them difficult to analyse and predict. Correspondingly, in ABS, as well as explicitly specified behaviours of individual agents, higher level behaviours can emerge spontaneously from agent action sequences and agent-agent interactions. We have previously introduced the complex event formalism for specifying emergent behaviours in dynamically executing ABS [5], [6]. Based on the formalism, we also described a method for detecting and analysing emergent behaviours in multi-agent simulations, giving us an effective means of studying and more reliably predicting these systems. Complex event types define sets of multi-dimensional structures of interrelated events arising from the actions of one or more agents. They are therefore directly related to the agent specifications, which determine the behaviour of individual agents. Although the abstract constructs of the formalism have already been introduced in [5] and [6], they have not yet been related to a specific agentbased specification language. Here, we define the constructs in terms of the X-machine formalism, which is widely used to specify multi-agent systems. This extends the existing X-machine framework to model higher level emergent behaviours as well as agent-level state transitions. Thus, emergent behaviours at any level of abstraction can be specified for detection and analysis in a dynamically executing ABS. ∗Department of Computer Science, University College London, [email protected] (corresponding author) †Department of Oncology, UCL Cancer Institute and UCL Research Department of Structural and Molecular Biology, [email protected] ‡Department of Computer Science, University College London, [email protected]