Abstract
Reciprocal cooperation is prevalent in human society. Understanding human reciprocal cooperation in human-agent interaction can help design human-agent systems that promote cooperation and joint performance. Studies have found that people reciprocate cooperative behavior when interacting with computer agents in social dilemma games. However, few studies have investigated human reciprocal cooperation with agents in complex dynamic environments. This article examines the behavioral and neurological patterns of reciprocal cooperation in a hospital management microworld experiment. The participants ( n = 30) work with both high- and low-cooperation computer agents to share resources to cope with dynamic demands. Participants’ resource sharing behaviors were recorded and their prefrontal cortex (PFC) activation was measured using functional near-infrared spectroscopy (fNIRS) technology. Similar to previous studies conducted with participants in the United States, results demonstrate that participants in China showed reciprocal cooperation behaviors with the agents. Specifically, participants share more resources and achieve higher performance when working with a high-cooperation agent than with a low-cooperation agent. A high activation level is detected in the right dorsolateral PFC when working with a high-cooperation agent. Other PFC activation patterns imply that cooperation could be unnecessarily mentally taxing in certain situations. These findings suggest that human cooperativeness in human–agent systems can be calibrated by an agent's cooperation behavior. System designers should design for appropriate cooperativeness and avoid the inefficient use of system resources. Neurological measures could be a useful tool to investigate the mental process in human-agent cooperation
Highlights
A DVANCES in artificial intelligence technologies have led to a paradigm shift from human–machine interaction to human–machine cooperation and human-agent cooperation [1], Manuscript received September 16, 2019; revised March 5, 2020; accepted April 19, 2020
The purpose of this study is to investigate the reciprocal cooperation in human-agent interaction in dynamic tasks
3) Other Notable Results: Tests done with linear mixed effects (LME) Model #3 revealed that participants’ reciprocal cooperation behavior was moderated by demand tempo
Summary
A DVANCES in artificial intelligence technologies have led to a paradigm shift from human–machine interaction to human–machine cooperation and human-agent cooperation [1], Manuscript received September 16, 2019; revised March 5, 2020; accepted April 19, 2020. In human–machine systems with intelligent agents, challenges for researchers and practitioners’ work are changing from how to design display and control interface to how to design social behaviors, such as effective communication [3] and teamwork [4]. In such systems, the relationship between humans and agents is more likely to be lateral coordination than hierarchical human supervisory control. One of the psychological factors that influence cooperation is reciprocal cooperation, which is a social norm that humans tend to return favors [7], [8]. This study used neurological measures to explore the neurological characteristics that underlie reciprocal cooperation behaviors
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