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Patrick M. Pilarski

◀ ▶ joint publications with Johannes Günther 0002

> Home > Persons > Patrick M. Pilarski

Publications

2022
[j12]
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  - journals/frai/KearneyGP22
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  - https://dblp.org/rec/journals/frai/KearneyGP22
Alex Kearney, Johannes Günther, Patrick M. Pilarski:
Prediction, Knowledge, and Explainability: Examining the Use of General Value Functions in Machine Knowledge. Frontiers Artif. Intell. 5: 826724 (2022)
[c27]
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  - conf/collas/KearneyK0P22
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Alex Kearney, Anna Koop, Johannes Günther, Patrick M. Pilarski:
What Should I Know? Using Meta-Gradient Descent for Predictive Feature Discovery in a Single Stream of Experience. CoLLAs 2022: 604-616
[c25]
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  - conf/icorr/WilliamsGHPS22
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Heather E. Williams, Johannes Günther, Jacqueline S. Hebert, Patrick M. Pilarski, Ahmed W. Shehata:
Composite Recurrent Convolutional Neural Networks Offer a Position-Aware Prosthesis Control Alternative While Balancing Predictive Accuracy with Training Burden. ICORR 2022: 1-6
[i31]
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  - journals/corr/abs-2205-10407
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Nadia M. Ady, Roshan Shariff, Johannes Günther, Patrick M. Pilarski:
Prototyping three key properties of specific curiosity in computational reinforcement learning. CoRR abs/2205.10407 (2022)
[i30]
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  - journals/corr/abs-2206-06485
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Alexandra Kearney, Anna Koop, Johannes Günther, Patrick M. Pilarski:
What Should I Know? Using Meta-gradient Descent for Predictive Feature Discovery in a Single Stream of Experience. CoRR abs/2206.06485 (2022)
[i26]
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  - journals/corr/abs-2212-00187
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Nadia M. Ady, Roshan Shariff, Johannes Günther, Patrick M. Pilarski:
Five Properties of Specific Curiosity You Didn't Know Curious Machines Should Have. CoRR abs/2212.00187 (2022)
2021
[i24]
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  - journals/corr/abs-2111-11212
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  - https://dblp.org/rec/journals/corr/abs-2111-11212
Alex Kearney, Anna Koop, Johannes Günther, Patrick M. Pilarski:
Finding Useful Predictions by Meta-gradient Descent to Improve Decision-making. CoRR abs/2111.11212 (2021)
2020
[j8]
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  - journals/firai/GuntherAKDP20
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Johannes Günther, Nadia M. Ady, Alex Kearney, Michael Rory Dawson, Patrick M. Pilarski:
Examining the Use of Temporal-Difference Incremental Delta-Bar-Delta for Real-World Predictive Knowledge Architectures. Frontiers Robotics AI 7: 34 (2020)
[c23]
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  - conf/aaai/SherstanDM0P20
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Craig Sherstan, Shibhansh Dohare, James MacGlashan, Johannes Günther, Patrick M. Pilarski:
Gamma-Nets: Generalizing Value Estimation over Timescale. AAAI 2020: 5717-5725
2019
[c22]
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  - conf/atal/GuntherKADP19
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Johannes Günther, Alex Kearney, Nadia M. Ady, Michael Rory Dawson, Patrick M. Pilarski:
Meta-learning for Predictive Knowledge Architectures: A Case Study Using TIDBD on a Sensor-rich Robotic Arm. AAMAS 2019: 1967-1969
[i16]
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  - journals/corr/abs-1905-13268
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Johannes Günther, Elias Reichensdörfer, Patrick M. Pilarski, Klaus Diepold:
General Dynamic Neural Networks for explainable PID parameter tuning in control engineering: An extensive comparison. CoRR abs/1905.13268 (2019)
[i15]
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  - journals/corr/abs-1908-05751
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Johannes Günther, Nadia M. Ady, Alex Kearney, Michael Rory Dawson, Patrick M. Pilarski:
Examining the Use of Temporal-Difference Incremental Delta-Bar-Delta for Real-World Predictive Knowledge Architectures. CoRR abs/1908.05751 (2019)
[i14]
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  dblp key:
  - journals/corr/abs-1911-07794
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Craig Sherstan, Shibhansh Dohare, James MacGlashan, Johannes Günther, Patrick M. Pilarski:
Gamma-Nets: Generalizing Value Estimation over Timescale. CoRR abs/1911.07794 (2019)

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