Bob and Alice Go to a Bar: Reasoning About Future With Probabilistic Programs

David Tolpin, Tomer Dobkin

Research output: Working paper/PreprintPreprint

Abstract

Agent preferences should be specified stochastically rather than deterministically.
Planning as inference with stochastic preferences naturally describes agent behaviors, does not require introducing rewards and exponential weighing of behaviors, and allows to reason about agents using the solid foundation of Bayesian statistics. Stochastic conditioning is the formalism behind agents with stochastic preferences.
Original languageEnglish GB
StatePublished - 2021

Publication series

NamearXiv preprint arXiv:2108.03834

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