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Uncertainty in Artificial Intelligence (UAI 2008)

Combinatorial Prediction Markets

author: Robin Hanson, George Mason University

Description

Several hundred organizations are now using prediction markets to forecast sales, project completion dates, and more. This number has been doubling annually for several years. Most, however, are simple prediction markets, with one market per number forecast, and several traders per market. In contrast, a single combinatorial prediction market lets a few traders manage an entire combinatorial space of forecasts. For millions of numbers or less, implementation is easy, and lab experiments have confirmed feasibility and accuracy. For larger spaces, however, many open computational problems remain.

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Slides
0:00 Combinatorial Prediction Markets
0:11 What Do “We” Believe?
3:05 Buy Low, Sell High
5:38 Today’s Current Event Prices
6:54 Beats Alternatives
8:09 Prediction Market Accuracy in the Long Run
8:34 Policy Analysis Market
9:04 The Fuss
10:28 Companies that Have Implemented an Internal Prediction Market
10:55 Internal Applications
11:19 Prediction Markets
12:07 Not Experts vs. Self-Chosen Amateurs
13:12 Advantages
13:52 Ad Agency Decision Markets
16:04 Corporate Applications
16:48 Decision Market Requirements
16:56 - Questions
20:02 - Questions
21:10 Combo Betting
24:39 Sport Finals Tickets
26:07 PAM Scenario
27:37 Some Consensus Mechanisms
28:26 Old Tech Meets New
29:44 Opinion Pool “Impossibile”
30:01 Best of Both
34:35 Quantal Response Modularity
34:53 Laboratory Tests
35:30 Environments: Goals, Training
37:42 Experiment Environment
38:06 MSR Info vs. Time – 3 Variables
38:32 MSR Info vs. Time – 255 Prices
38:43 Combinatorial Lab Experiments
39:21 Combo Market Maker Best of 5 Mechs
39:31 Compute Tasks
44:54 - Questions

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