Software Agents Can Help Time-Stressed Teams

Penn State researchers have developed software agents which can help human teams to react more accurately and quickly in time-stressed situations than human teams acting alone. According to this news release, the software was tested in a military command-and-control simulation. "When time pressures were normal, the human teams functioned well, sharing information and making correct decisions about the potential threat." But when the pressure increased, the human teams made errors who would have cost lives in real situations. The decisions taken by agent-supported human teams were much better. Now, it remains to be seen if this software can be used in other stressful situations, such as for emergency management operations. Read more...

Here is a description of the simulation experiment.
In the simulation, team members had to protect an airbase and supply route which were under attack by enemy aircraft. The scenarios were configured with different patterns of attack and at different tempos. The situation was complicated because team members had to determine at first if the aircraft were neutral or hostile. Furthermore, two team members were dependent on the third whose role was to gather information and communicate it to them.
"When the teams don't know if the incoming aircraft is the enemy, the defense team can't attack, and the supply team takes action to avoid the incoming threat which causes a delay in delivery," said Shuang Sun[, one of the researchers.] "These decisions lower the performance of the whole team."
When the information gatherer was supported by the researchers' R-CAST software system, the information was gathered and shared more quickly. As a result, the human-agent teams were better able to defend themselves from enemy attack and deliver supplies without delay, Sun said.

The illustration below shows the structure of the two teams used for testing, with human teams on the left, and agent-supported human teams on the right (Credit: Penn State).


And the diagram below shows how these different teams were able to destroy enemies when stress increased (Credit: Penn State).


It seems pretty obvious that software agents helped humans to better react in this stressful situation.

The researchers, Xiaocong Fan, Shuang Sun, John Yen, and Michael McNeese, have presented the results of their experiments at the Fourth International Joint Conference on Autonomous Agents and Multi-Agent Systems, which was held in Amsterdam on July 25-29, 2005 (AAMAS 2005).

Here is a link to their full paper named "Extending the Recognition-Primed Decision Model to Support Human-Agent Collaboration" (PDF format, 8 pages, 413 KB). Here are some selected excerpts from the introduction.
The aim of this research is to support human decision making teams using cognitive agents empowered by a collaborative Recognition-Primed Decision (RPD) model. In this paper, we ¯rst describe an RPD-enabled agent architecture (R-CAST), in which we have implemented an internal mechanism of decision-making adaptation based on collaborative expectancy monitoring, and an information exchange mechanism driven by relevant cue analysis.
We have evaluated R-CAST agents in a real-time simulation environment, feeding teams with frequent decision-making tasks under different tempo situations. While the result conforms to psychological findings that human team members are extremely sensitive to their workload in high-tempo situations, it clearly indicates that human teams, when supported by R-CAST agents, can perform better in the sense that they can maintain team performance at acceptable levels in high time pressure situations.