modeling uncertain domains with polyagents
Agents are a powerful tool for systems modeling. Instantiating each domain entity with an agent captures many aspects of system dynamics and interactions that other modeling techniques do not. However, an entity's agent can execute only one trajectory per run, and so does not capture the alternative trajectories accessible in the evolution of any realistic system. Averaging over multiple runs does not capture the range of individual interactions. We address these problems with a new modeling construct, the polyagent , which represents each entity with a single persistent avatar supported by a swarm of transient ghosts . Each ghost interacts with the ghosts of other avatars through digital pheromone fields, capturing a wide range of alternative trajectories in a single run of the system that can proceed faster than real time.
dynamics digital pheromones uncertainty swarm intelligence bdi multiple future