Source Themes

A Probabilistic Interpretation of Self-Paced Learning with Applications to Reinforcement Learning

Pascal Klink, Hany Abdulsamad, Boris Belousov, Carlo D'Eramo, Jan Peters, Joni Pajarinen

Convex Regularization in Monte-Carlo Tree Search

Tuan Q Dam, Carlo D'Eramo, Jan Peters, Joni Pajarinen

Self-Paced Deep Reinforcement Learning

Pascal Klink, Carlo D'Eramo, Jan Peters, Joni Pajarinen

Generalized Mean Estimation in Monte-Carlo Tree Search

Tuan Dam, Pascal Klink, Carlo D'Eramo, Jan Peters, Joni Pajarinen

Multi-agent active information gathering in discrete and continuous-state decentralized POMDPs by policy graph improvement

Mikko Lauri, Joni Pajarinen, Jan Peters

Probabilistic approach to physical object disentangling

Joni Pajarinen, Oleg Arenz, Jan Peters, Gerhard Neumann

Compatible natural gradient policy search

Joni Pajarinen, Hong Linh Thai, Riad Akrour, Jan Peters, Gerhard Neumann

Projections for Approximate Policy Iteration Algorithms

Riad Akrour, Joni Pajarinen, Jan Peters, Gerhard Neumann

Learning Intention Aware Online Adaptation of Movement Primitives

Dorothea Koert, Joni Pajarinen, Albert Schotschneider, Susanne Trick, Constantin Rothkopf, Jan Peters

An Algorithmic Perspective on Imitation Learning

Takayuki Osa, Joni Pajarinen, Gerhard Neumann, J Andrew Bagnell, Pieter Abbeel, Jan Peters