This paper tackles the problem of active perception: taking actions to minimize one’s uncertainty. It further formalizes the link between information gain and prediction rewards, and uses this to propose a deep-learning approach to optimize active perception from a data set, thus obviating the need for a complex POMDP model.
Aleksander Czechowski got his paper on Decentralized MCTS via Learned Teammate Models accepted at IJCAI 2020.
In this paper we learn the models of other agents that each agent then uses to predict the future with. Stay tuned for the camready.