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2020 – today
- 2024
[i7]Irina Jurenka, Markus Kunesch, Kevin R. McKee, Daniel Gillick, Shaojian Zhu, Sara Wiltberger, Shubham Milind Phal, Katherine L. Hermann, Daniel Kasenberg, Avishkar Bhoopchand, Ankit Anand, Miruna Pîslar, Stephanie Chan, Lisa Wang, Jennifer She, Parsa Mahmoudieh, Aliya Rysbek, Wei-Jen Ko, Andrea Huber, Brett Wiltshire, Gal Elidan, Roni Rabin, Jasmin Rubinovitz, Amit Pitaru, Mac McAllister, Julia Wilkowski, David Choi, Roee Engelberg, Lidan Hackmon, Adva Levin, Rachel Griffin, Michael Sears, Filip Bar, Mia Mesar, Mana Jabbour, Arslan Chaudhry, James Cohan, Sridhar Thiagarajan, Nir Levine, Ben Brown, Dilan Görür, Svetlana Grant, Rachel Hashimshoni, Laura Weidinger, Jieru Hu, Dawn Chen, Kuba Dolecki, Canfer Akbulut, Maxwell L. Bileschi, Laura Culp, Wen-Xin Dong, Nahema Marchal, Kelsie Van Deman, Hema Bajaj Misra, Michael Duah, Moran Ambar, Avi Caciularu, Sandra Lefdal, Christopher Summerfield, James An, Pierre-Alexandre Kamienny, Abhinit Mohdi, Theofilos Strinopoulous, Annie Hale, Wayne Anderson, Luis C. Cobo, Niv Efron, Muktha Ananda, Shakir Mohamed, Maureen Heymans, Zoubin Ghahramani, Yossi Matias, Ben Gomes, Lila Ibrahim:
Towards Responsible Development of Generative AI for Education: An Evaluation-Driven Approach. CoRR abs/2407.12687 (2024)- 2021
- [j1]Thomas Arnold
, Daniel Kasenberg, Matthias Scheutz:
Explaining in Time: Meeting Interactive Standards of Explanation for Robotic Systems. ACM Trans. Hum. Robot Interact. 10(3): 25:1-25:23 (2021) - [c11]Vasanth Sarathy, Daniel Kasenberg, Shivam Goel, Jivko Sinapov, Matthias Scheutz:
SPOTTER: Extending Symbolic Planning Operators through Targeted Reinforcement Learning. AAMAS 2021: 1118-1126 - 2020
- [c10]Daniel Kasenberg, Ravenna Thielstrom, Matthias Scheutz:
Generating Explanations for Temporal Logic Planner Decisions. ICAPS 2020: 449-458 - [c9]David Buckingham, Daniel Kasenberg, Matthias Scheutz:
Simultaneous Representation of Knowledge and Belief for Epistemic Planning with Belief Revision. KR 2020: 172-181 - [i6]Vasanth Sarathy, Daniel Kasenberg, Shivam Goel, Jivko Sinapov, Matthias Scheutz:
SPOTTER: Extending Symbolic Planning Operators through Targeted Reinforcement Learning. CoRR abs/2012.13037 (2020)
2010 – 2019
- 2019
- [c8]Daniel Kasenberg, Antonio Roque, Ravenna Thielstrom, Meia Chita-Tegmark, Matthias Scheutz:
Generating justifications for norm-related agent decisions. INLG 2019: 484-493 - [i5]Daniel Kasenberg, Antonio Roque, Ravenna Thielstrom, Meia Chita-Tegmark, Matthias Scheutz:
Generating Justifications for Norm-Related Agent Decisions. CoRR abs/1911.00226 (2019) - [i4]Daniel Kasenberg, Antonio Roque, Ravenna Thielstrom, Matthias Scheutz:
Engaging in Dialogue about an Agent's Norms and Behaviors. CoRR abs/1911.00229 (2019) - 2018
- [c7]Daniel Kasenberg, Matthias Scheutz:
Norm Conflict Resolution in Stochastic Domains. AAAI 2018: 85-92 - [c6]Daniel Kasenberg, Matthias Scheutz:
Inverse Norm Conflict Resolution. AIES 2018: 178-183 - [c5]Daniel Kasenberg, Thomas Arnold, Matthias Scheutz:
Norms, Rewards, and the Intentional Stance: Comparing Machine Learning Approaches to Ethical Training. AIES 2018: 184-190 - [c4]Daniel Kasenberg:
Learning and Obeying Conflicting Norms in Stochastic Domains. AIES 2018: 370-371 - [c3]Daniel Kasenberg:
Inferring and Obeying Norms in Temporal Logic. HRI (Companion) 2018: 301-302 - [i3]Daniel Kasenberg, Vasanth Sarathy, Thomas Arnold, Matthias Scheutz, Tom Williams:
Quasi-Dilemmas for Artificial Moral Agents. CoRR abs/1807.02572 (2018) - 2017
- [c2]Thomas Arnold, Daniel Kasenberg, Matthias Scheutz:
Value Alignment or Misalignment - What Will Keep Systems Accountable? AAAI Workshops 2017 - [c1]Daniel Kasenberg, Matthias Scheutz:
Interpretable apprenticeship learning with temporal logic specifications. CDC 2017: 4914-4921 - [i2]Daniel Kasenberg, Matthias Scheutz:
Stochastic Planning with Conflicting Temporal Logic Goals. CoRR abs/1706.07448 (2017) - [i1]Daniel Kasenberg, Matthias Scheutz:
Interpretable Apprenticship Learning with Temporal Logic Specifications. CoRR abs/1710.10532 (2017)
Coauthor Index
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