Procrastination with Variable Present Bias
Talkat Optimization and Decision-Making Under Uncertainty (Simons Institute, September 2016) · 2016-09-19..09-23·
summary
Introduces variable present bias: each day the bias B is drawn IID (example: 1/3 chance B=1, 2/3 chance B=3). Proves a main lemma that worst-case task graphs reduce to a worst-case two-level graph and uses an iterative construction plus a Myerson pricing reduction to show menu-like choices suffice. Gives bounds: with bounded-distance graphs the procrastination ratio is Theta(n) (tight via a marathon-training construction); with monotone distance and enough mass near B=1 the ratio is constant.
AI-written summary · about
chapters (6)
- 0:00Introduction
- 1:30Task graphs and discounting
- 10:06Procrastination ratios
- 10:22Theoretical models and results
- 27:41Conclusion and summary
- 30:12Questions and answers
related talks
01h 12mA Brief Introduction to Algorithms, Game Theory and Risk-Averse Decision Making
48mA Simple Condition for Constant Regret in Online Decision-Making
01h 10mMulti-Dimensional and Non-Linear Mechanism Design and Approximation II
40mApproximation Algorithms for Optimization under Uncertainty
31mBatch Value-function Approximation with Only Realizability
43mLearning about Auctions
47mExploiting Combinatorial Structure in Constraint Programming: ...
33mA Few Connections Between Optimization and Probability
