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Found 4 papers, 2 papers with code
Minimax-Bayes Reinforcement Learning
While the Bayesian decision-theoretic framework offers an elegant solution to the problem of decision making under uncertainty, one question is how to appropriately select the prior distribution.
Inferential Induction: A Novel Framework for Bayesian Reinforcement Learning
Bayesian reinforcement learning (BRL) offers a decision-theoretic solution for reinforcement learning.
Do Kernel and Neural Embeddings Help in Training and Generalization?
The approximated representations induced by these kernels are fed to the neural network and the optimization and generalization properties of the final model are evaluated and compared.
Learning to Play Guess Who? and Inventing a Grounded Language as a Consequence
The images from the game provide a non trivial environment for the agents to discuss and a natural grounding for the concepts they decide to encode in their communication.
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