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Sriram Gopalakrishnan
Sriram Gopalakrishnan
JP Morgan AI Research
Verified email at asu.edu
Title
Cited by
Cited by
Year
Digital messages in a load control system
BM Courtney, T Gill, S Gopalakrishnan, RA Shah, V Sukumar, MS Taipale, ...
US Patent 9,985,436, 2018
312018
Automated learning of hierarchical task networks for controlling minecraft agents
C Nguyen, N Reifsnyder, S Gopalakrishnan, H Munoz-Avila
2017 IEEE Conference on Computational Intelligence and Games (CIG), 226-231, 2017
162017
On the constrained time-series generation problem
A Coletta, S Gopalakrishnan, D Borrajo, S Vyetrenko
Advances in Neural Information Processing Systems 36, 2024
92024
Goal recognition via model-based and model-free techniques
D Borrajo, S Gopalakrishnan, VK Potluru
1st Workshop on Planning for Financial Services (FinPlan) at ICAPS 2021, 2020
92020
Recognizing plans by learning embeddings from observed action distributions
Y Zha, Y Li, S Gopalakrishnan, B Li, S Kambhampati
Proceedings of the 17th International Conference on Autonomous Agents and …, 2017
82017
Word2htn: Learning task hierarchies using statistical semantics and goal reasoning
S Gopalakrishnan, H Munoz-Avila, U Kuter
4th Workshop on Goal Reasoning (IJCAI’16), 2016
82016
pyrddlgym: From rddl to gym environments
A Taitler, M Gimelfarb, J Jeong, S Gopalakrishnan, M Mladenov, X Liu, ...
In the Workshop on Planning and Reinforcement Learning (PRL) at ICAPS 2023, 2022
72022
Synthesizing Policies That Account For Human Execution Errors Caused By State-Aliasing In Markov Decision Processes
S Gopalakrishnan, M Verma, S Kambhampati
4th Workshop on Explainable AI Planning (XAIP) at ICAPS 2021, https …, 2021
62021
Learning task hierarchies using statistical semantics and goal reasoning
S Gopalakrishnan, H Muñoz-Avila, U Kuter
AI Communications 31 (2), 167-180, 2018
62018
Computing Policies That Account For The Effects Of Human Agent Uncertainty During Execution In Markov Decision Processes
S Gopalakrishnan, M Verma, S Kambhampati
5th Workshop on Explainable AI Planning (XAIP) at ICAPS 2022, 2021
52021
Embedding directed graphs in potential fields using FastMap-D
S Gopalakrishnan, L Cohen, S Koenig, TK Kumar
Proceedings of the International Symposium on Combinatorial Search 11 (1), 48-56, 2020
52020
Minimizing Robot Navigation-Graph For Position-Based Predictability By Humans
S Gopalakrishnan, S Kambhampati
Proceedings of the 21st International Conference on Autonomous Agents and …, 2020
4*2020
TGE-viz: Transition Graph Embedding for Visualization of Plan Traces and Domains
S Gopalakrishnan, S Kambhampati
Extended Abstract and Demo at International Conference on Automated Planning …, 2018
4*2018
An architecture for novelty handling in a multi-agent stochastic environment: Case study in open-world monopoly
T Thai, M Shen, N Varshney, S Gopalakrishnan, U Soni, C Baral, ...
Designing Artificial Intelligence for Open Worlds: Papers from the 2022 …, 2022
32022
FinRDDL: Can AI Planning be used for Quantitative Finance Problems?
S Patra, M Mahfouz, S Gopalakrishnan, D Magazzeni, M Veloso
FinPlan 2023, 36, 2023
22023
Assignment and Prioritization of Tasks with Uncertain Durations for Satisfying Makespans in Decentralized Execution
S Gopalakrishnan, D Borrajo
Proceedings of the International Conference on Automated Planning and …, 2022
12022
Integrating Planning, Execution and Monitoring in the presence of Open World Novelties: Case Study of an Open World Monopoly Solver
S Gopalakrishnan, U Soni, T Thai, P Lymperopoulos, M Scheutz, ...
5th Workshop on Integrated Planning, Acting, and Execution (IntEx) at ICAPS …, 2021
12021
Digital messages in a load control system
BM Courtney, T Gill, S Gopalakrishnan, RA Shah, V Sukumar, MS Taipale, ...
US Patent 10,651,653, 2020
12020
Exploration of DQN in ViZDoom
S Freitas, A Dudley, S Gopalakrishnan, J Feinglass, B Clayton
12018
Learning Hierarchical Task Networks Using Semantic Word Embeddings
S Gopalakrishnan
Lehigh University (MSc. thesis), 2017
12017
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