Trust-based role coordination in task-oriented multiagent systems

摘要

In Task-oriented MultiAgent Systems (T-MAS) with a heterogeneous population, deciding with whom to interact is a particularly difficult issue for an agent, as repeated interactions with the same agents might be scarce, and reputation mechanisms become increasingly unreliable. In this work, we present a mechanism (REM) which can be used by agents in a T-MAS to take more informed decisions regarding partner selection, and thus to improve their individual utilities. This mechanism monitors the interactions in the T-MAS, evolves a role taxonomy, and assigns agents to roles based on their observed performance in different types of tasks. This information can be used by agents to better estimate the expected behaviour of potential counterparts in future interactions. We thus highlight the descriptive features of roles, providing expectations of the behaviour of agents in certain types of tasks, rather than their normative facets. We empirically show that the use of the mechanism helps agents select better partners for their interactions than selection processes based only on the agents’ own experience. This is especially significant for new agents that join a system.