This chapter concludes a two part series which examines the emergent properties of multi-agent communication in “temporally asynchronous” environments. Many traditional agent and swarm simulation environments divide time into discrete “ticks” where all entity behavior is synchronized to a master “world clock”. In other words, all agent behavior is governed by a single timer where all agents act and interact within deterministic time intervals. This discrete timing mechanism produces a somewhat restricted and artificial model of autonomous agent interaction. In addition to the behavioral autonomy normally associated with agents, simulated agents should also have “temporal autonomy” in order to interact realistically. This chapter focuses on the exploration of a grid of specially embedded, message-passing agents, where each message represents the communication of a core “belief”. Here, we focus our attention on the how the temporal variance of belief propagation from individual agents induces emergent and dynamic effects on a global population.
Message Driven Communication
Thus far, we have focused on the exploration of the globally emergent behaviors in passive agent interaction systems. The agents reacted to their environment, but did so in a manner where each agent’s vivification was independent of neighboring vivifications. In the message based version of this simulation, the focus shifts from agents behaving passively within the environment into a model where each agent actively attempts to exert influence over the environment. The emergent behaviors observed in previous sections resulted from agents examining their immediate surroundings and updating themselves accordingly. Global behavior arose from the non-deterministic agent vivification order and the asynchronous nature of the updates. In this set of experiments, global emergence is driven by the exchange of messages.
In this section, we expanded our simulation to accommodate active agents which directly communicate—albeit in a primitive manner. Information is exchanged as simple messages which are reflective of an agent’s internal state. Though agents may take on many states during a simulation, each agent communicates its active state with its spatially embedded neighbors. The active model is divided into two distinct subtypes. The first subtype, discussed in Section “Message Driven Game of Life”, is a direct extension of the previous “Conway” model; but agents respond to events generated by neighbors rather than vivificating autonomously. The second subtype, discussed in Section “Fuzzy ‘Belief’ Promulgation”, is a completely new model based upon temporally variant “belief” interaction. The models in both subtypes display interesting and rather unique behavioral characteristics.