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Found 2 papers, 1 papers with code
Bob and Alice Go to a Bar: Reasoning About Future With Probabilistic Programs
Reinforcement learning via inference with stochastic preferences naturally describes agent behaviors, does not require introducing rewards and exponential weighing of trajectories, and allows to reason about agents using the solid foundation of Bayesian statistics.
Stochastic Probabilistic Programs
We introduce the notion of a stochastic probabilistic program and present a reference implementation of a probabilistic programming facility supporting specification of stochastic probabilistic programs and inference in them.
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