Travelled to:1 × Canada
1 × Finland
1 × France
1 × Germany
1 × Sweden
1 × Taiwan
1 × United Kingdom
2 × USA
Collaborated with:A.Y.Ng T.M.Moldovan S.Patil K.S.Narayan A.Punjani A.Coates M.Quigley K.Goldberg S.McKinley A.Garg M.Laskey J.Mahler J.Schulman S.Levine M.I.Jordan P.Moritz S.Sen A.Murali D.Lee Haoran Tang Jeffrey O. Zhang Huazhe Xu T.Darrell Menglong Guo Philipp Wu Brent Yi David V. Gealy T.Siauw J.A.M.Cunha I.Hsu J.Pouliot Z.McCarthy F.T.Pokorny J.P.v.d.Berg D.Kragic R.Kapadia K.A.Nichols S.Lim A.M.Okamura S.Krishnan B.Kehoe J.Wang M.Franklin K.Y.Goldberg
Talks about:learn (8) reinforc (4) control (3) robot (3) use (3) apprenticeship (2) process (2) explor (2) model (2) data (2)
Person: Pieter Abbeel
DBLP: Abbeel:Pieter
Contributed to:
2015
20152014201320122008200620052004
20182019Wrote 13 papers:
- CASE-2015-LaskeyMMPPBKAG #2d #modelling #multi #nondeterminism
- Multi-armed bandit models for 2D grasp planning with uncertainty (ML, JM, ZM, FTP, SP, JPvdB, DK, PA, KG), pp. 572–579.
- CASE-2015-McKinleyGSKMNLP #single use
- A single-use haptic palpation probe for locating subcutaneous blood vessels in robot-assisted minimally invasive surgery (SM, AG, SS, RK, AM, KAN, SL, SP, PA, AMO, KG), pp. 1151–1158.
- ICML-2015-NarayanPA #metaprogramming
- α-β Divergences Discover Micro and Macro Structures in Data (KSN, AP, PA), pp. 796–804.
- ICML-2015-SchulmanLAJM #optimisation #policy #trust
- Trust Region Policy Optimization (JS, SL, PA, MIJ, PM), pp. 1889–1897.
- CASE-2014-MahlerKLSMKPWFAG #learning #process #using
- Learning accurate kinematic control of cable-driven surgical robots using data cleaning and Gaussian Process Regression (JM, SK, ML, SS, AM, BK, SP, JW, MF, PA, KYG), pp. 532–539.
- CASE-2013-GargPSCHAPG #3d #algorithm
- An algorithm for computing customized 3D printed implants with curvature constrained channels for enhancing intracavitary brachytherapy radiation delivery (AG, SP, TS, JAMC, ICH, PA, JP, KG), pp. 466–473.
- ICML-2012-MoldovanA #markov #process
- Safe Exploration in Markov Decision Processes (TMM, PA), p. 188.
- ICML-2008-CoatesAN #learning #multi
- Learning for control from multiple demonstrations (AC, PA, AYN), pp. 144–151.
- ICML-2006-AbbeelQN #learning #modelling #using
- Using inaccurate models in reinforcement learning (PA, MQ, AYN), pp. 1–8.
- ICML-2005-AbbeelN #learning
- Exploration and apprenticeship learning in reinforcement learning (PA, AYN), pp. 1–8.
- ICML-2004-PieterN #learning
- Apprenticeship learning via inverse reinforcement learning (PA, AYN).
- AIIDE-2018-LeeTZXDA #architecture #composition #learning
- Modular Architecture for StarCraft II with Deep Reinforcement Learning (DL, HT, JOZ, HX, TD, PA), pp. 187–193.
- CASE-2019-GuoWYGMA #low cost #robust
- Blue Gripper: A Robust, Low-Cost, and Force-Controlled Robot Hand (MG, PW, BY, DVG, SM, PA), pp. 1505–1510.