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AI apology: interactive multi-objective reinforcement learning for human-aligned AI.

, , , , и . Neural Comput. Appl., 35 (23): 16917-16930 (августа 2023)

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Richard Janissen

Biomolecular based nano-manipulation with a combined atomic force microscope and single molecule fluorescence setup. Uni Düsseldorf, (2009)

Richard Reisdorf

Richard Beck

Richard Donderer

Richard Scheel

 

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Evaluating authorship distance methods using the positive Silhouette coefficient., , и . Nat. Lang. Eng., 19 (4): 517-535 (2013)Rated MCRDR: Finding non-Linear Relationships Between Classifications in MCRDR., и . HIS, том 105 из Frontiers in Artificial Intelligence and Applications, стр. 499-508. IOS Press, (2003)Fault-tolerant data aggregation scheme for monitoring of critical events in grid based healthcare sensor networks., , и . SpringSim (HPC), стр. 56-64. SCS/ACM, (2011)Overcoming weaknesses of density peak clustering using a data-dependent similarity measure., , , и . Pattern Recognit., (мая 2023)Explainable robotic systems: Interpreting outcome-focused actions in a reinforcement learning scenario., , и . CoRR, (2020)A practical guide to multi-objective reinforcement learning and planning., , , , , , , , , и 8 other автор(ы). Auton. Agents Multi Agent Syst., 36 (1): 26 (2022)Elastic Step DQN: A novel multi-step algorithm to alleviate overestimation in Deep QNetworks., , , , и . CoRR, (2022)Towards a Broad-Persistent Advising Approach for Deep Interactive Reinforcement Learning in Robotic Environments., , и . Sensors, 23 (5): 2681 (марта 2023)Non-functional regression: A new challenge for neural networks., , , и . Neurocomputing, (2018)Empirical evaluation methods for multiobjective reinforcement learning algorithms., , , , и . Mach. Learn., 84 (1-2): 51-80 (2011)