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5 papers · 1 filter
Using Adaptive Experiments to Rapidly Help Students
Angela Zavaleta-Bernuy, Qi Yin Zheng, Hammad Shaikh +4
Adaptive experiments can increase the chance that current students obtain better outcomes from a field experiment of an instructional intervention. In such experiments, the probabi…
Reinforcement Learning for Education: Opportunities and Challenges
Adish Singla, Anna N. Rafferty, Goran Radanovic +1
This survey article has grown out of the RL4ED workshop organized by the authors at the Educational Data Mining (EDM) 2021 conference. We organized this workshop as part of a commu…
Challenges in Statistical Analysis of Data Collected by a Bandit Algorithm: An Empirical Exploration in Applications to Adaptively Randomized Experiments
Joseph Jay Williams, Jacob Nogas, Nina Deliu +4
Multi-armed bandit algorithms have been argued for decades as useful for adaptively randomized experiments. In such experiments, an algorithm varies which arms (e.g. alternative in…
Game Level Clustering and Generation using Gaussian Mixture VAEs
Zhihan Yang, Anurag Sarkar, Seth Cooper
Variational autoencoders (VAEs) have been shown to be able to generate game levels but require manual exploration of the learned latent space to generate outputs with desired attri…
Controllable Level Blending between Games using Variational Autoencoders
Anurag Sarkar, Zhihan Yang, Seth Cooper
Previous work explored blending levels from existing games to create levels for a new game that mixes properties of the original games. In this paper, we use Variational Autoencode…