Forecast Hedging, Calibration, And Game Equilibria

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United States Simons Institute for the Theory of Computing
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Published on ● Video Link: https://www.youtube.com/watch?v=kNHJcQTeRDM


Duration: 1:21:40
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18

Sergiu Hart (Hebrew University of Jerusalem)
https://simons.berkeley.edu/talks/forecast-hedging-calibration-and-game-equilibria
Learning in the Presence of Strategic Behavior

Calibration means that forecasts and average realized frequencies are close. We develop the concept of "forecast hedging", which consists of choosing the forecasts so as to guarantee that the expected track record can only improve. This yields all the calibration results by the same simple basic argument, while differentiating between them by the forecast-hedging tools used: deterministic and fixed point-based versus stochastic and minimax-based. Additional contributions are an improved definition of continuous calibration, ensuing game dynamics that yield Nash equilibria in the long run, and a new calibrated forecasting procedure for binary events that is simpler than all known such procedures.



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Tags:
Simons Institute
theoretical computer science
UC Berkeley
Computer Science
Theory of Computation
Theory of Computing
Learning in the Presence of Strategic Behavior
Sergiu Hart