The economics of regret on Science

This week Science publishes yet another paper on neuroeconomics. In Predicting Human Interactive Learning by Regret-Driven Neural Networks, Davide Marchiori and Massimo Warglien incorporated regret in a relatively simple model. They showed that their model fits well the behavior of players in 21 different economic experiments. Marchiori and Warglien defined regret as the difference between the outcome the actor choice yielded and the best outcome that could have been attained if the actor had made a different choice.

References

Marchiori Davide and Warglien Massimo (2008) Predicting Human Interactive Learning by Regret-Driven Neural Networks, Science, 22 February 2008; Vol 319, no 5866, pp.1111-1113 abstract

Cohen, MIchael, D. (2008) Learning with regret, Science, 22 February 2008; Vol 319, no 5866, pp.1052-1053.

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