Abstract
In many scenarios, humans must team with agents to achieve joint aims. When working collectively in a team of human and artificial agents, communication is important to establish a shared situation of the task at hand. With no human in the loop and little cost for communication, information about the task can be easily exchanged. However, when communication becomes expensive, or when there are humans in the loop, the strategy for sharing information must be carefully designed: too little information leads to lack of shared situation awareness, while too much overloads the human team members, decreasing performance overall. This paper investigates the effects of sharing beliefs and goals in agent teams and in human-agent teams. We performed a set of experiments using the BlocksWorlds for Teams (BW4T) testbed to assess different strategies for information sharing. In previous experimental studies using BW4T, explanations about agent behaviour were shown to have no effect on team performance. One possible reason for this is because the existing scenarios in BW4T contained joint tasks, but not joint actions. That is, atomic actions that required interdependent and simultaneous action between more than one agent. We implemented new scenarios in BW4T in which some actions required two agents to complete. Our results showed an improvement in artificial-agent team performance when communicating goals and sharing beliefs, but with goals contributing more to team performance, and that in human-agent teams, communicating only goals was more effective than communicating both goals and beliefs.
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Notes
- 1.
Artificial agents are also programmed with this capability in our model.
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Acknowledgements
The authors thank Christian Muise for his valuable feedback on drafts of this paper. This research is partially funded by Australian Research Council Discovery Grant DP130102825: Foundations of Human-Agent Collaboration: Situation-Relevant Information Sharing.
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Li, S., Sun, W., Miller, T. (2016). Communication in Human-Agent Teams for Tasks with Joint Action. In: Dignum, V., Noriega, P., Sensoy, M., Sichman, J. (eds) Coordination, Organizations, Institutions, and Norms in Agent Systems XI. COIN 2015. Lecture Notes in Computer Science(), vol 9628. Springer, Cham. https://doi.org/10.1007/978-3-319-42691-4_13
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