22 citations · 26 across the 2 of their papers we have counts for
3 papers · 1 filter
Human-Level Reinforcement Learning through Theory-Based Modeling, Exploration, and Planning
Pedro A. Tsividis, Joao Loula, Jake Burga +5
Reinforcement learning (RL) studies how an agent comes to achieve reward in an environment through interactions over time. Recent advances in machine RL have surpassed human expert…
How do Humans Understand Explanations from Machine Learning Systems? An Evaluation of the Human-Interpretability of Explanation
Menaka Narayanan, Emily Chen, Jeffrey He +3
Recent years have seen a boom in interest in machine learning systems that can provide a human-understandable rationale for their predictions or decisions. However, exactly what ki…
Estimating scale-invariant future in continuous time
Zoran Tiganj, Samuel J. Gershman, Per B. Sederberg +1
Natural learners must compute an estimate of future outcomes that follow from a stimulus in continuous time. Widely used reinforcement learning algorithms discretize continuous tim…