Decentralised Detection of Emergence in Complex Adaptive Systems

Abstract

This paper describes Decentralised Emergence Detection (DETect), a novel distributed algorithm that enables agents to collaboratively detect emergent events in Complex Adaptive Systems (CAS). Nondeterministic interactions between agents in CAS can give rise to emergent behaviour or properties at the system level. The nature, timing and consequence of emergence is unpredictable and may be harmful to the system or individual agents. DETect relies on the feedback that occurs from the system level (macro) to the agent level (micro) when emergence occurs. This feedback constrains agents at the micro-level, and results in changes occurring in the relationship between an agent and its environment. DETect uses statistical methods to automatically select the properties of the agent and environment to monitor, and tracks the relationship between these properties over time. When a significant change is detected, the algorithm uses distributed consensus to determine if a sufficient number of agents have simultaneously experienced a similar change. On agreement of emergence, DETect raises an event, which its agent or other interested observers can use to act appropriately. The approach is evaluated using a multi-agent case study.

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“…Emergence detection can be formulated as an online changepoint detection (CPD) problem by regarding the time steps when emergence forms or evaporates as change points [7,8]. As shown in Figure 1(b), the number of congested streets can serve as a global variable to monitor the emergence.…”

“…Therefore, methods requiring all agents' states to compute a global metric for emergence detection become impractical under the distributed setting. Hence, it is desirable to detect emergence using agents' local observation, which is feasible because all agents experience the downward causation [7] when the emergence forms, as shown in Figure 1(a). For example, cars slow down in a crowded street.…”

“…For example, cars slow down in a crowded street. Based on this observation, O'toole et al [7] propose DETect, the only feasible emergence detection method for the distributed setting. In DETect, each agent analyzes its relationship with neighbors, communicates with them, and sends feedback when finding a noticeable change in the relationship.…”

“…DETect [7], the only existing method from class III, overcomes the limitations of the first two classes. Each agent serves as a local detector, and agents' feedback is aggregated to monitor the emergence.…”

“…Many real-world dynamic systems can be regarded as complex adaptive systems (CASs) composed of autonomous, adaptive, and interacting agents, whose interactions at the micro level can result in emergent phenomena at the macro level, namely, emergence [1][2][3]. Figure 1(a) presents an example.…”