We present four new reinforcement learning algorithms based on actor-critic and natural-gradient ideas, and provide their convergence proofs. Actor-critic reinforcement learning m...
Shalabh Bhatnagar, Richard S. Sutton, Mohammad Gha...
This paper investigates the application of randomized algorithms for large scale SVM learning. The key contribution of the paper is to show that, by using ideas random projections...
Abstract—In this paper, we present the analysis and experimental validation of a vision-aided inertial navigation algorithm for planetary landing applications. The system employs...
Anastasios I. Mourikis, Nikolas Trawny, Stergios I...
In recent years there has been a great deal of interest in "modular reinforcement learning" (MRL). Typically, problems are decomposed into concurrent subgoals, allowing ...
Sooraj Bhat, Charles Lee Isbell Jr., Michael Matea...
In group decision-making problems that involve selfinterested agents with private information, reaching socially optimal outcomes requires aligning the goals of individuals with t...