abstract bibtex

Abstract A Bayesian agent acting in a multi-agent environment learns to predict the other agents' policies if its prior assigns positive probability to them (in other words, its prior contains a grain of truth). Finding a reasonably large class of policies that contains the.

@Article{Leike, author = {Leike, J and Taylor, J and Fallenstein, B}, title = {A Formal Solution to the Grain of Truth Problem}, journal = {jan.leike.name}, volume = {}, number = {}, pages = {}, year = {}, abstract = {Abstract A Bayesian agent acting in a multi-agent environment learns to predict the other agents\' policies if its prior assigns positive probability to them (in other words, its prior contains a grain of truth). Finding a reasonably large class of policies that contains the.}, location = {}, keywords = {}}

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