Supplementary Material for "The Effects on Adaptive Behaviour of Negatively Valenced Signals in Reinforcement Learning" Navarro-GuerreroNicolás LoweRobert WermterStefan 2018 zip files with raw data from the 10 random initializations of the 4 best hyperparameter sets per condition and per activation function. Organized by function and per condition.<br><br>pdf file containing the pair-wise comparison of the three tested conditions against the baseline.<br><br><div>Link to the supplementary material of the original paper, includes matlab command and data set for learning:<br></div>https://figshare.com/s/becd4366e4ed38731353<div><br><div><b>References:<br></b></div><div>Navarro-Guerrero, N., Lowe, R., & Wermter, S. (2017). The Effects on Adaptive Behaviour of Negatively Valenced Signals in Reinforcement Learning. In Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EPIROB) (pp. 148–155). Lisbon, Portugal: IEEE. https://doi.org/10.1109/DEVLRN.2017.8329800<br></div><div><br></div><div>Navarro-Guerrero, N., Lowe, R., & Wermter, S. (2017). Improving Robot Motor Learning with Negatively Valenced Reinforcement Signals. Frontiers in Neurorobotics, 11(10). https://doi.org/10.3389/fnbot.2017.00010</div></div><div><br></div><div><div><b>Contact:</b></div><div>For information please see the paper. For specific questions regarding the paper please contact Nicolás Navarro-Guerrero.</div></div>