Johannes Günther

20 papers A* 1A 2B 1Journal 13Unranked 2

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	Explainability of deep reinforcement learning algorithms in robotic domains by using Layer-wise Relevance Propagation. Eng. Appl. Artif. Intell. Mehran Taghian, Shotaro Miwa, Yoshihiro Mitsuka, Johannes Günther, Shadan Golestan, Osmar R. Zaïane
2024	J	`jnl`	General value functions for fault detection in multivariate time series data. Frontiers Robotics AI Andy Wong, Mehran Taghian Jazi, Tomoharu Takeuchi, Johannes Günther, Osmar Zaïane
2023	A	`conf`	Multi-Robot Warehouse Optimization: Leveraging Machine Learning for Improved Performance. AAMAS Mara Cairo, Bevin Eldaphonse, Payam Mousavi, Sahir, Sheikh Jubair, Matthew E. Taylor, Graham Doerksen, Nikolai Kummer, Jordan Maretzki, Gupreet Mohhar, Sean Murphy, Johannes Günther, Laura Petrich, Talat Syed
2022	J	`jnl`	Affordance as general value function: a computational model. Adapt. Behav. Daniel Graves, Johannes Günther, Jun Luo
2022	—	`conf`	Composite Recurrent Convolutional Neural Networks Offer a Position-Aware Prosthesis Control Alternative While Balancing Predictive Accuracy with Training Burden. ICORR Heather E. Williams, Johannes Günther, Jacqueline S. Hebert, Patrick M. Pilarski, Ahmed W. Shehata
2022	J	`jnl`	Five Properties of Specific Curiosity You Didn't Know Curious Machines Should Have. CoRR Nadia M. Ady, Roshan Shariff, Johannes Günther, Patrick M. Pilarski
2022	J	`jnl`	Prediction, Knowledge, and Explainability: Examining the Use of General Value Functions in Machine Knowledge. Frontiers Artif. Intell. Alex Kearney, Johannes Günther, Patrick M. Pilarski
2022	J	`jnl`	Prototyping three key properties of specific curiosity in computational reinforcement learning. CoRR Nadia M. Ady, Roshan Shariff, Johannes Günther, Patrick M. Pilarski
2022	—	`conf`	What Should I Know? Using Meta-Gradient Descent for Predictive Feature Discovery in a Single Stream of Experience. CoLLAs Alex Kearney, Anna Koop, Johannes Günther, Patrick M. Pilarski
2022	J	`jnl`	What Should I Know? Using Meta-gradient Descent for Predictive Feature Discovery in a Single Stream of Experience. CoRR Alexandra Kearney, Anna Koop, Johannes Günther, Patrick M. Pilarski
2021	J	`jnl`	Finding Useful Predictions by Meta-gradient Descent to Improve Decision-making. CoRR Alex Kearney, Anna Koop, Johannes Günther, Patrick M. Pilarski
2020	J	`jnl`	Affordance as general value function: A computational model. CoRR Daniel Graves, Johannes Günther, Jun Luo
2020	J	`jnl`	Examining the Use of Temporal-Difference Incremental Delta-Bar-Delta for Real-World Predictive Knowledge Architectures. Frontiers Robotics AI Johannes Günther, Nadia M. Ady, Alex Kearney, Michael Rory Dawson, Patrick M. Pilarski
2020	A*	`conf`	Gamma-Nets: Generalizing Value Estimation over Timescale. AAAI Craig Sherstan, Shibhansh Dohare, James MacGlashan, Johannes Günther, Patrick M. Pilarski
2019	B	`conf`	Detecting the Onset of Machine Failure Using Anomaly Detection Methods. DaWaK Mohammad Riazi, Osmar R. Zaïane, Tomoharu Takeuchi, Anthony Maltais, Johannes Günther, Micheal Lipsett
2019	J	`jnl`	Examining the Use of Temporal-Difference Incremental Delta-Bar-Delta for Real-World Predictive Knowledge Architectures. CoRR Johannes Günther, Nadia M. Ady, Alex Kearney, Michael Rory Dawson, Patrick M. Pilarski
2019	J	`jnl`	Gamma-Nets: Generalizing Value Estimation over Timescale. CoRR Craig Sherstan, Shibhansh Dohare, James MacGlashan, Johannes Günther, Patrick M. Pilarski
2019	J	`jnl`	General Dynamic Neural Networks for explainable PID parameter tuning in control engineering: An extensive comparison. CoRR Johannes Günther, Elias Reichensdörfer, Patrick M. Pilarski, Klaus Diepold
2019	A	`conf`	Meta-learning for Predictive Knowledge Architectures: A Case Study Using TIDBD on a Sensor-rich Robotic Arm. AAMAS Johannes Günther, Alex Kearney, Nadia M. Ady, Michael Rory Dawson, Patrick M. Pilarski
2018	—	`—`	Machine intelligence for adaptable closed loop and open loop production engineering systems. Johannes Günther