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Nonparametric General Reinforcement Learning
Jan Leike
Reinforcement learning (RL) problems are often phrased in terms of Markov decision processes (MDPs). In this thesis we go beyond MDPs and consider RL in environments that are non-M…
Geometric Nontermination Arguments
Jan Leike, Matthias Heizmann
We present a new kind of nontermination argument, called geometric nontermination argument. The geometric nontermination argument is a finite representation of an infinite executio…
A Formal Solution to the Grain of Truth Problem
Jan Leike, Jessica Taylor, Benya Fallenstein
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 conta…
Exploration Potential
Jan Leike
We introduce exploration potential, a quantity that measures how much a reinforcement learning agent has explored its environment class. In contrast to information gain, exploratio…