Norm Enforcement with a Soft Touch: Faster Emergence, Happier Agents
CoRR(2024)
摘要
A multiagent system can be viewed as a society of autonomous agents, whose
interactions can be effectively regulated via social norms. In general, the
norms of a society are not hardcoded but emerge from the agents' interactions.
Specifically, how the agents in a society react to each other's behavior and
respond to the reactions of others determines which norms emerge in the
society. We think of these reactions by an agent to the satisfactory or
unsatisfactory behaviors of another agent as communications from the first
agent to the second agent. Understanding these communications is a kind of
social intelligence: these communications provide natural drivers for norm
emergence by pushing agents toward certain behaviors, which can become
established as norms. Whereas it is well-known that sanctioning can lead to the
emergence of norms, we posit that a broader kind of social intelligence can
prove more effective in promoting cooperation in a multiagent system.
Accordingly, we develop Nest, a framework that models social intelligence in
the form of a wider variety of communications and understanding of them than in
previous work. To evaluate Nest, we develop a simulated pandemic environment
and conduct simulation experiments to compare Nest with baselines considering a
combination of three kinds of social communication: sanction, tell, and hint.
We find that societies formed of Nest agents achieve norms faster; moreover,
Nest agents effectively avoid undesirable consequences, which are negative
sanctions and deviation from goals, and yield higher satisfaction for
themselves than baseline agents despite requiring only an equivalent amount of
information.
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