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1. Using Team Discussions to Understand Behavior in Indefinitely Repeated Prisoner’s Dilemma Games

   David J. Cooper; John H. Kagel (November 2023, American economic journal Microeconomics)

   We compare behavior of two person teams with individuals in indefinitely repeated prisoner dilemma games with perfect monitoring. Team discussions are used to understand the rationale underlying these choices, and how these choices come about. There are three main findings: (1) Teams learned to cooperate faster than individuals, and cooperation was more stable for teams. (2) Strategies identified from team dialogues differ from those identified by the Strategy Frequency Estimation Method. This reflects the improvisational nature of teams’ decision making. (3) Increasing cooperation was primarily driven by teams unilaterally cooperating in the hope of inducing their opponent to cooperate. 

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2. Using Team Discussions to Understand Behavior in Indefinitely Repeated Prisoner’s Dilemma Games

   David j. Cooper; John H. Kagel (November 2023, American economic journal Microeconomics)

   We compare behavior of two person teams with individuals in indefinitely repeated prisoner dilemma games with perfect monitoring. Team discussions are used to understand the rationale underlying these choices, and how these choices come about. There are three main findings: (1) Teams learned to cooperate faster than individuals, and cooperation was more stable for teams. (2) Strategies identified from team dialogues differ from those identified by the Strategy Frequency Estimation Method. This reflects the improvisational nature of teams’ decision making. (3) Increasing cooperation was primarily driven by teams unilaterally cooperating in the hope of inducing their opponent to cooperate. 

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3. Using team discussions to understand behavior in indefinitely repeated prisoner dilemma games

   John H. Kagel; David J Cooper (August 2024, American economic journal Microeconomics)

   We compare behavior of two person teams with individuals in indefinitely repeated prisoner dilemma games with perfect monitoring. Team discussions are used to understand the rationale underlying these choices, and how these choices come about. There are three main findings: (1) Teams learned to cooperate faster than individuals, and cooperation was more stable for teams. (2) Strategies identified from team dialogues differ from those identified by the Strategy Frequency Estimation Method. This reflects the improvisational nature of teams’ decision making. (3) Increasing cooperation was primarily driven by teams unilaterally cooperating in the hope of inducing their opponent to cooperate. 

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4. Ad Hoc Teaming Through Evolution

   Cook, Joshua; Tumer, Kagan (July 2021, Genetic and evolutionary computation)

   null (Ed.)

   Cooperative Co-evolutionary Algorithms effectively train policies in multiagent systems with a single, statically defined team. However, many real-world problems, such as search and rescue, require agents to operate in multiple teams. When the structure of the team changes, these policies show reduced performance as they were trained to cooperate with only one team. In this work, we solve the cooperation problem by training agents to fill the needs of an arbitrary team, thereby gaining the ability to support a large variety of teams. We introduce Ad hoc Teaming Through Evolution (ATTE) which evolves a limited number of policy types using fitness aggregation across multiple teams. ATTE leverages agent types to reduce the dimensionality of the interaction search space, while fitness aggregation across teams selects for more adaptive policies. In a simulated multi-robot exploration task, ATTE is able to learn policies that are effective in a variety of teaming schemes, improving the performance of CCEA by a factor of up to five times. 

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5. A new measure for team performance: Measuring inter-brain synchrony of engineering students when designing and building

   Aruon, A.; Shealy, T.; Gero, J. (June 2023, Engineering project organization journal)

   This research paper examines the patterns of inter-brain synchrony among engineering student teams and the relationship between inter-brain synchrony and team cooperation and performance. A pilot study was conducted with eight two-person teams of fourth-year undergraduate civil engineering students. Three collaborative design and build tasks were assigned to each team. Two independent raters carried out the behavioral analysis, scoring team cooperation. Each team member wore a functional near-infrared spectroscopy (fNIRS) device to measure inter-brain synchrony during the tasks. The results showed that inter-brain synchrony occurred during the team task, but the patterns varied between groups and tasks. Elevated levels of inter-brain synchrony were observed in the left ventrolateral prefrontal cortex (VLPFC) and left dorsolateral prefrontal cortex (DLPFC). The left VLPFC and left DLPFC are often associated with cognitive processes such as problem-solving, working memory, decision-making, and coordinated verbal exchange. Inter-brain synchrony was positively correlated with task performance and cooperation when teams were asked to design and build a structure given limited time and money but negatively correlated with cooperation and performance on other more open-ended design sketching tasks. The study’s findings suggest that inter-brain synchrony exists when engineering students work together as a team, but the results are inconsistent between task types. Inter-brain synchrony could be a useful metric for measuring team cooperation and performance, particularly in tasks that require coordinated verbal exchange, problemsolving, and decision-making. However, the study’s small sample size limits the generalizability of the results. Future studies with a larger sample size and more diverse groups of engineers are needed to validate the findings and explore their implications further. 

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