System performance in multi-agent resource allocation systems can often improve if individual agents reduce their activity. Agents in such systems need a way to modulate their individual behavior in the light of the system’s state, preferably in a way that does not require centralized control. We illustrate the problem of hyperactive agents in two domains related to resource allocation. We describe a simple, decentralized scheme, inspired by insect pheromones, that enables individual agents to adjust their level of activity as the system operates, and discuss a general approach to dealing with approaching deadlines. Then we demonstrate the effectiveness of these mechanisms in the two example domains. Categories and Subject Descriptors I.2.11 [Distributed Artificial Intelligence]: Coherence and coordination; Multiagent systems. General Terms Algorithms, Performance, Experimentation. Keywords Digital pheromones, machine learning, adaptation, resource allocation, complexity, dynamics
H. Van Dyke Parunak, Sven Brueckner, Robert S. Mat