BEST POSTER AWARD WINNER

Intrinsically-Motivated Robot Learning of Bayesian Probabilistic Movement Primitives

by

Thibaut Kulak and Sylvain Calinon

ACCEPTED PAPERS

Session I

I.1. Learning to Explore a Class of Multiple Reward-Free Environments

          Mirco Mutti, Mattia Mancassola, and Marcello Restelli

I.2. The Significance of Reward in Reward-Based Exploration

           David Isele

I.3. Curious exploration in complex environments based on Hopfield networks

           Menachem Stern, Clélia de Mulatier, Philipp Fleig, and Vijay Balasubramanian

I.4. Interest-Driven Exploration for Real Robot Applications: Sample-Efficiency, High Accuracy, and Robustness

           Rania Rayyes, Heiko Donat, and Jochen Steil

I.5. Intrinsically-Motivated Robot Learning of Bayesian Probabilistic Movement Primitives 

           Thibaut Kulak and Sylvain Calinon

I.6. Making Curiosity Explicit in Vision-based RL

           Elie Aljalbout, Maximilian Ulmer, and Rudolph Triebel

I.7. Self-Improving Semantic Perception for Indoor Localisation

           Hermann Blum, Francesco Milano, René Zurbrügg, Roland Siegwart, Cesar Cadena, and Abel Gawel

Session II

II.1. Curiosity-Driven Learning of Abstract Plan Feasibility

             Michael Noseworthy, Caris Moses, Isaiah Brand, Sebastian Castro, Leslie Kaelbling, Tomas Lozano-Pérez, and Nicholas Roy

II.2. Learning Novel Objects Continually Through Curiosity

             Ali Ayub and Alan R. Wagner

II.3. Curiosity-Driven Decision-Making for Autonomous Robots in Uncertain Environments

Ran Tian, Haiming Gang, and David Isele

II.4. Influencing Behavioral Attributions to Robot Motion During Task Execution

             Nick Walker, Christoforos Mavrogiannis, Siddhartha Srinivasa, and Maya Cakmak

II.5. Fractional Binding in Vector Symbolic Representations for Efficient Mutual Information Exploration

             P. Michael Furlong, Terrence C. Stewart, and Chris Eliasmith

II.6. Curiosity in Path-Planning: Synthesizing Path-Planners for Efficient Exploration

             Lucas Saldyt and Heni Ben Amor

II.7. Adversarial Intrinsic Motivation for Reinforcement Learning

             Ishan Durugkar, Scott Niekum, and Peter Stone