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cs.LG2023
Divide and Repair: Using Options to Improve Performance of Imitation Learning Against Adversarial Demonstrations
Prithviraj Dasgupta
We consider the problem of learning to perform a task from demonstrations given by teachers or experts, when some of the experts' demonstrations might be adversarial and demonstrat…
cs.LG2023★ 1 cited
Synthetically Generating Human-like Data for Sequential Decision Making Tasks via Reward-Shaped Imitation Learning
Bryan Brandt, Prithviraj Dasgupta
We consider the problem of synthetically generating data that can closely resemble human decisions made in the context of an interactive human-AI system like a computer game. We pr…
cs.LG2020★ 2 cited
Playing to Learn Better: Repeated Games for Adversarial Learning with Multiple Classifiers
Prithviraj Dasgupta, Joseph B. Collins, Michael McCarrick
We consider the problem of prediction by a machine learning algorithm, called learner, within an adversarial learning setting. The learner's task is to correctly predict the class…