Sarath Sreedharan
Sarath Sreedharan
Assistant Professor, CSU
Verified email at - Homepage
Cited by
Cited by
Plan explanations as model reconciliation: Moving beyond explanation as soliloquy
T Chakraborti, S Sreedharan, Y Zhang, S Kambhampati
arXiv preprint arXiv:1701.08317, 2017
Plan explicability and predictability for robot task planning
Y Zhang, S Sreedharan, A Kulkarni, T Chakraborti, HH Zhuo, ...
2017 IEEE international conference on robotics and automation (ICRA), 1313-1320, 2017
Large Language Models Still Can't Plan (A Benchmark for LLMs on Planning and Reasoning about Change)
K Valmeekam, A Olmo, S Sreedharan, S Kambhampati
arXiv preprint arXiv:2206.10498, 2022
Explicability? legibility? predictability? transparency? privacy? security? the emerging landscape of interpretable agent behavior
T Chakraborti, A Kulkarni, S Sreedharan, DE Smith, S Kambhampati
Proceedings of the international conference on automated planning and …, 2019
The emerging landscape of explainable ai planning and decision making
T Chakraborti, S Sreedharan, S Kambhampati
arXiv preprint arXiv:2002.11697, 2020
Plan explanations as model reconciliation--an empirical study
T Chakraborti, S Sreedharan, S Grover, S Kambhampati
2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI …, 2019
On the planning abilities of large language models (a critical investigation with a proposed benchmark)
K Valmeekam, S Sreedharan, M Marquez, A Olmo, S Kambhampati
arXiv preprint arXiv:2302.06706, 2023
Hierarchical Expertise Level Modeling for User Specific Contrastive Explanations.
S Sreedharan, S Srivastava, S Kambhampati
IJCAI, 4829-4836, 2018
Handling model uncertainty and multiplicity in explanations via model reconciliation
S Sreedharan, S Kambhampati
Proceedings of the International Conference on Automated Planning and …, 2018
Projection-aware task planning and execution for human-in-the-loop operation of robots in a mixed-reality workspace
T Chakraborti, S Sreedharan, A Kulkarni, S Kambhampati
2018 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2018
Why can't you do that hal? explaining unsolvability of planning tasks
S Sreedharan, S Srivastava, D Smith, S Kambhampati
International Joint Conference on Artificial Intelligence, 2019
Radar—a proactive decision support system for human-in-the-loop planning
S Sengupta, T Chakraborti, S Sreedharan, SG Vadlamudi, ...
2017 AAAI Fall Symposium Series, 2017
Alternative modes of interaction in proximal human-in-the-loop operation of robots
T Chakraborti, S Sreedharan, A Kulkarni, S Kambhampati
arXiv preprint arXiv:1703.08930, 2017
GPT3-to-plan: Extracting plans from text using GPT-3
A Olmo, S Sreedharan, S Kambhampati
arXiv preprint arXiv:2106.07131, 2021
Symbols as a lingua franca for bridging human-ai chasm for explainable and advisable ai systems
S Kambhampati, S Sreedharan, M Verma, Y Zha, L Guan
Proceedings of the AAAI Conference on Artificial Intelligence 36 (11), 12262 …, 2022
Leveraging pre-trained large language models to construct and utilize world models for model-based task planning
L Guan, K Valmeekam, S Sreedharan, S Kambhampati
Advances in Neural Information Processing Systems 36, 79081-79094, 2023
Foundations of explanations as model reconciliation
S Sreedharan, T Chakraborti, S Kambhampati
Artificial Intelligence 301, 103558, 2021
–d3wa+–a case study of xaip in a model acquisition task for dialogue planning
S Sreedharan, T Chakraborti, C Muise, Y Khazaeni, S Kambhampati
Proceedings of the International Conference on Automated Planning and …, 2020
Balancing explicability and explanation in human-aware planning
S Sreedharan, S Kambhampati
2017 AAAI Fall Symposium Series, 2017
Robust planning with incomplete domain models
T Nguyen, S Sreedharan, S Kambhampati
Artificial Intelligence 245, 134-161, 2017
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