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Katherine Driggs-Campbell — most-cited papers & profile · Reinforcement Learning
← authors
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overview
Katherine Driggs-Campbell
29
papers ·
25
citations
Google Scholar ↗
Semantic Scholar ↗
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Most-cited papers
Monte-Carlo Tree Search for Policy Optimization
2019 · 5 citations
Decentralized Structural-RNN for Robot Crowd Navigation with Deep Reinforcement Learning
2020 · 2 citations
Improved Robustness and Safety for Autonomous Vehicle Control with Adversarial Reinforcement Learning
2019 · 1 citations
Combining Planning and Deep Reinforcement Learning in Tactical Decision Making for Autonomous Driving
2019
Off Environment Evaluation Using Convex Risk Minimization
2021
Marginalized Importance Sampling for Off-Environment Policy Evaluation
2023
Towards Provable Log Density Policy Gradient
2024
Structured Graph Network for Constrained Robot Crowd Navigation with Low Fidelity Simulation
2024
HEIGHT: Heterogeneous Interaction Graph Transformer for Robot Navigation in Crowded and Constrained Environments
2024
Top co-authors
Shuijing Liu
· 4
Neeloy Chakraborty
· 3
Pulkit Katdare
· 3
Kaiwen Hong
· 2
Mykel J. Kochenderfer
· 2
Xiaobai Ma
· 2
Anant A. Joshi
· 1
and Mykel J. Kochenderfer
· 1
Carl-Johan Hoel
· 1
Fatemeh Cheraghi Pouria
· 1
Haochen Xia
· 1
Joydeep Biswas
· 1
Topics
Model-Based RL
Multi-Agent
Safe RL
Policy Gradient
Offline RL
Game AI
Value-Based
Exploration