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Improving Learnt Local MAPF Policies with Heuristic Search

Published in ICAPS, 2024

Using heuristic search to post-process the outputs of ML MAPF systems. We found that this approach significantly improved the scalability of ML methods!

Recommended citation: Veerapaneni, R., Wang, Q., Ren, K., Jakobsson, A., Li, J., & Likhachev, M. (2024, May). Improving Learnt Local MAPF Policies with Heuristic Search. In Proceedings of the International Conference on Automated Planning and Scheduling (Vol. 34, pp. 597-606).
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Decision-focused evaluation of worst-case distribution shift

Published in UAI, 2024

A novel formulation of distribution shift to identify worst-case shifts w.r.t. decision-focused loss functions.

Recommended citation: Ren, K., Byun, Y., & Wilder, B. (2024). Decision-focused evaluation of worst-case distribution shift. arXiv preprint arXiv:2407.03557.
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Work Smarter Not Harder: Simple Imitation Learning with CS-PIBT Outperforms Large Scale Imitation Learning for MAPF

Published in ICRA, 2024

Follow-up paper on MAPF, doing large-scale training of GNNs for MAPF for improved scalability

Recommended citation: Veerapaneni, R., Jakobsson, A., Ren, K., Kim, S., Li, J., & Likhachev, M. (2024). Work Smarter Not Harder: Simple Imitation Learning with CS-PIBT Outperforms Large Scale Imitation Learning for MAPF. arXiv preprint arXiv:2409.14491.
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Talk 1 on Relevant Topic in Your Field

Published: March 01, 2012

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Tutorial 1 on Relevant Topic in Your Field

Published: March 01, 2013

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Talk 2 on Relevant Topic in Your Field

Published: February 01, 2014

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Conference Proceeding talk 3 on Relevant Topic in Your Field

Published: March 01, 2014

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Teaching experience 1

Undergraduate course, University 1, Department, 2014

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Teaching experience 2

Workshop, University 1, Department, 2015

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