How Automated Agents Treat Humans and Other Automated Agents in Situations of Inequity: An Experimental Study
Ron Katz and Sarit Kraus
In: AAMAS-08, 12-16 May 2008, Estoril, Portugal.
This paper explores the question of how agent designers perceive
and treat their agent’s opponents. In particular, it examines the in-
fluence of the opponent’s identity (human vs. automated agent)
in negotiations. We empirically demonstrate that when people interact
spontaneously they treat human opponents differently than
automated agents in the context of equity and fairness considerations.
However, these difference vanish when people design and
implement agents that will interact on their behalf. Nevertheless,
the commitment of the agents to honor agreements with people is
higher than their commitment to other agents. In the experiments,
which comprised 147 computer science students, we used the Colored
Trails game as the negotiation environment. We suggest possible
explanations for the relationships among online players, agent
designers, human opponents and automated opponents.