Decision Making under Uncertainty Jun zhu AI Lab, Tsinghua University http://cs.cmu.edu/-iunzhu Nov6.2011
Jun Zhu AI Lab, Tsinghua University http://cs.cmu.edu/~junzhu Nov 6, 2011 Decision Making under Uncertainty
Decision Making is Ubiquitous THE PERKS OF ONLINE STOCK INVESTING determining which decision. from a set of Pe ossible alternatives, is optimal MLA 2011, Tsinghua university
Decision Making is Ubiquitous determining which decision, from a set of possible alternatives, is optimal 2 MLA 2011, Tsinghua University
Two Challenges o The set of outcomes can be large and complex a The agent must weigh different factors in determining the most referred outcomes a E. g, when deciding which job to take we must consider o Work time, amount of salary, company reputation, officemates utility Theor e The outcome of an action is not fully determined a We must consider the probabilities of various outcomes and the preferences of the agent between these outcomes Probability Theory MLA 2011, Tsinghua University
Two Challenges The set of outcomes can be large and complex ❑ The agent must weigh different factors in determining the most preferred outcomes ❑ E.g., when deciding which job to take we must consider: Work time, amount of salary, company reputation, officemates, … The outcome of an action is not fully determined ❑ We must consider the probabilities of various outcomes and the preferences of the agent between these outcomes Utility Theory Probability Theory 3 MLA 2011, Tsinghua University
Decision Theory o the theory of statistical decision functions [Wald, 1950 +.. is concerned with the process of making decisions and explicitly includes the payoffs that may result determining which decision, from a set of possible alternatives, is optimal for a particular set of conditions MLA 2011, Tsinghua University
Decision Theory the theory of statistical decision functions [Wald, 1950] … is concerned with the process of making decisions and explicitly includes the payoffs that may result ❑ determining which decision, from a set of possible alternatives, is optimal for a particular set of conditions 4 MLA 2011, Tsinghua University
Decision Making in Statistical Learning o distribution-free only training examples are provided a use data to estimate the complete distribution, and then derive decision rule( density estimation is hard P(a Cu) a use training examples to directly make decision, e. g, empirical risk minimization o DT: assumes the complete data distribution is qiven MLA 2011, Tsinghua University
Decision Making in Statistical Learning distribution-free; only training examples are provided ❑ use data to estimate the complete distribution, and then derive decision rule (density estimation is hard!) ❑ use training examples to directly make decision, e.g., empirical risk minimization DT: assumes the complete data distribution is given 5 MLA 2011, Tsinghua University