Don't use chartgpt Scoring rule based Peer PredictionConsider three experts who received the following signals and have the following posterior (i.e.conditional) probabilities about the signals of a peer agent.expert signal P(0) P(1)a100.7 0.3a210.40.6a300.70.3Give each expert's score being matched each of the other two experts as well as their subjectiveexpected score for scoring rules based peer prediction using the log score. That is, calculate theexpert's expected score with respect to the expert's posterior belief about other experts she maybe matched with.

To calculate the scores and expected scores for each expert using the log score in the scoring rule…

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Operations Research : Applications and Algorithms

4th Edition

ISBN:9780534380588

Author:Wayne L. Winston

Publisher:Wayne L. Winston

Chapter17: Markov Chains

Section17.5: Steady-state Probabilities And Mean First Passage Times

Problem 10P

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Consider an agent that controls the traffic lights at a 4-way intersection (where 2 roads cross, with traffic flowing in all directions). The lights have green/yellow/red main lights plus a left-turn arrow and a pedestrian indicator. The agent controls which lights go on and how long they stay on. Assume the intersection has signals for pedestrians and in-pavement detectors right before the crosswalk for cars and bikes. PEAS Description: Performance: answers could include safety (number of accidents at the intersection) and minimizing average wait time (e.g. per car, bike, pedestrian) Environment: roads, cars, pedestrians, etc. Actuators: the traffic lights: green/yellow/red/arrow/walk/don’t-walk in each of the 4 directions Sensors: in-pavement traffic detectors (bike and car), pedestrian signal buttons Design Rule based rational agent for the implementation of the given scenario
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