Ronald Ortner

Optimal Behavior is Easier to Learn than the Truth

2016 · Minds and Machines

We consider a reinforcement learning setting where the learner is given a set of possible models containing the true model. While there are algorithms that are able to successfully learn optimal behavior in this setting, …

Autonomous exploration for navigating in non-stationary CMPs

2019 · arXiv (Cornell University)

We consider a setting in which the objective is to learn to navigate in a controlled Markov process (CMP) where transition probabilities may abruptly change. For this setting, we propose a performance measure called exploration …