TY - JOUR
T1 - Automated agents' behavior in the Trust-Revenge game in comparison to other cultures
AU - Azaria, Amos
AU - Richardson, Ariella
AU - Elmalech, Avshalom
AU - Rosenfeld, Avi
PY - 2014/1/1
Y1 - 2014/1/1
N2 - Copyright © 2014, International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved. Agents that interact with humans are known to benefit from modeling them. Therefore, when designing agents intended for interaction with automated agents, it is crucial to model the other agents. However, little is known about how to model automated agents and in particular non-expert agents. Are automated agents to be modeled the same way that an agent models humans? Or does a separate model for interacting with automated agents need to be developed? We evaluate automated agent behavior (for non-expert agents) using a game called the Trust-Revenge game, which is known in social science for capturing different human tendencies. The Trust-Revenge game has a unique sub game-perfect equilibrium, however, very rarely do people follow it. We compared the behavior of automated agents to that of human actions in several demographic groups (including a group which is similar but not identical to the designers of the automated agents). We show that differences between automated agents' and humans' behavior are similar to differences between different human cultures.
AB - Copyright © 2014, International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved. Agents that interact with humans are known to benefit from modeling them. Therefore, when designing agents intended for interaction with automated agents, it is crucial to model the other agents. However, little is known about how to model automated agents and in particular non-expert agents. Are automated agents to be modeled the same way that an agent models humans? Or does a separate model for interacting with automated agents need to be developed? We evaluate automated agent behavior (for non-expert agents) using a game called the Trust-Revenge game, which is known in social science for capturing different human tendencies. The Trust-Revenge game has a unique sub game-perfect equilibrium, however, very rarely do people follow it. We compared the behavior of automated agents to that of human actions in several demographic groups (including a group which is similar but not identical to the designers of the automated agents). We show that differences between automated agents' and humans' behavior are similar to differences between different human cultures.
UR - http://www.scopus.com/inward/record.url?scp=84911458032&partnerID=8YFLogxK
M3 - ???researchoutput.researchoutputtypes.contributiontojournal.article???
VL - 2
JO - 13th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2014
JF - 13th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2014
ER -