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Reward-based decision making under social interaction

Reward-based decision making under social interaction. Damon Tomlin MURI Kick-Off meeting September 13, 2007. A. B. The decision task. The underlying structure . . . 1. 0.75. Reward A. 0.5. Reward B. Reward. Average. 0.25. 0. 0. 0.25. 0.5. 0.75. 1. % A.

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Reward-based decision making under social interaction

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  1. Reward-based decision making under social interaction Damon Tomlin MURI Kick-Off meeting September 13, 2007

  2. A B The decision task

  3. The underlying structure . . . 1 0.75 Reward A 0.5 Reward B Reward Average 0.25 0 0 0.25 0.5 0.75 1 % A

  4. A more interesting case . . . 1 0.75 Reward A Reward 0.5 Reward B Average 0.25 0 0 0.25 0.5 0.75 1 % A

  5. Adding social interaction . . . • Feedback • None • Choice history • Individual rewards

  6. Adding social interaction • Feedback • Different games • NEO data

  7. Conditions in the experiment: “Alone”

  8. Conditions in the experiment: “Rewards”

  9. Conditions in the experiment: “Choices”

  10. Logistics • Group size • Subject payment • Behavioral cohort • Imaging cohort

  11. Game elements • Crossing points • Optimal reward • Short term vs. long term gains

  12. 1 0.75 Reward A 0.5 Reward B Average 0.25 0 0 0.25 0.5 0.75 1 Games within the experiment "Simple" Rising Optimum Reward % A How frequently do subjects find the optimum? Once found, do they stay?

  13. Reward A Reward B Average Games within the experiment "Simple" Rising Optimum 1 0.75 Reward 0.5 0.25 0 0 0.25 0.5 0.75 1 % A Are subjects naturally biased toward A or B?

  14. Reward A Reward B Average Games within the experiment “Complex" Rising Optimum 1 0.75 Reward 0.5 0.25 0 0 0.25 0.5 0.75 1 % A Can subjects find a more subtle strategy? How do social partners affect adherence to it?

  15. Individual behavior

  16. Individual behavior

  17. Reward A Reward B Average Games within the experiment Converging Gaussians 1 0.75 Reward 0.5 0.25 0 0 0.25 0.5 0.75 1 % A How much exploration occurs in a simple task?

  18. Individual behavior

  19. Reward A Reward B Average Games within the experiment Diverging Gaussians 1 0.75 Reward 0.5 0.25 0 0 0.25 0.5 0.75 1 % A How does social information produce herd behavior?

  20. Individual behavior

  21. Summary • Binary choice decision paradigm • Social conditions: • Alone • Reward Information • Choice Information • Games examining: • Exploratory behavior • Herd behavior • Strategy maintenance

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