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2020 – today
- 2023
[i2]Bernhard Hengst, Maurice Pagnucco, David Rajaratnam, Claude Sammut, Michael Thielscher
:
Online Learning and Planning in Cognitive Hierarchies. CoRR abs/2310.12386 (2023)
2010 – 2019
- 2019
- [c27]Bernhard Hengst, Maurice Pagnucco, David Rajaratnam, Claude Sammut, Michael Thielscher:
Perceptual Context in Cognitive Hierarchies. Description Logic, Theory Combination, and All That 2019: 352-366 - 2018
- [i1]Bernhard Hengst, Maurice Pagnucco, David Rajaratnam, Claude Sammut, Michael Thielscher:
Perceptual Context in Cognitive Hierarchies. CoRR abs/1801.02270 (2018) - 2017
- [r2]Bernhard Hengst:
Hierarchical Reinforcement Learning. Encyclopedia of Machine Learning and Data Mining 2017: 611-619 - 2016
- [c26]David Rajaratnam, Bernhard Hengst, Maurice Pagnucco, Claude Sammut, Michael Thielscher:
Composability in Cognitive Hierarchies. Australasian Conference on Artificial Intelligence 2016: 42-55 - [c25]Keith Clark, Bernhard Hengst, Maurice Pagnucco, David Rajaratnam, Peter Robinson, Claude Sammut, Michael Thielscher:
A Framework for Integrating Symbolic and Sub-Symbolic Representations. IJCAI 2016: 2486-2492 - 2015
- [c24]Sean Harris, Bernhard Hengst, Maurice Pagnucco:
Termination Approximation: Continuous State Decomposition for Hierarchical Reinforcement Learning. AAAI Workshop: Knowledge, Skill, and Behavior Transfer in Autonomous Robots 2015 - [c23]Brad Hall, Sean Harris, Bernhard Hengst, Roger Liu, Kenneth Ng, Maurice Pagnucco, Luke Pearson, Claude Sammut, Peter Schmidt:
RoboCup SPL 2015 Champion Team Paper. RoboCup 2015: 72-82 - 2014
- [c22]Jayen Ashar, Jaiden Ashmore, Brad Hall, Sean Harris, Bernhard Hengst, Roger Liu, Jacky Zijie Mei, Maurice Pagnucco, Ritwik Roy, Claude Sammut, Oleg O. Sushkov, Belinda Teh, Luke Tsekouras:
RoboCup SPL 2014 Champion Team Paper. RoboCup 2014: 70-81 - 2013
- [c21]Peter Anderson, Youssef Hunter, Bernhard Hengst:
An ICP inspired inverse sensor model with unknown data association. ICRA 2013: 2713-2718 - [c20]Peter Anderson, Bernhard Hengst:
Fast Monocular Visual Compass for a Computationally Limited Robot. RoboCup 2013: 244-255 - 2012
- [c19]Bernhard Hengst:
On-Line Model-Based Continuous State Reinforcement Learning Using Background Knowledge. Australasian Conference on Artificial Intelligence 2012: 851-862 - [c18]Peter Anderson, Yongki Yusmanthia, Bernhard Hengst, Arcot Sowmya:
Robot Localisation Using Natural Landmarks. RoboCup 2012: 118-129 - [p1]Bernhard Hengst:
Hierarchical Approaches. Reinforcement Learning 2012: 293-323 - 2011
- [c17]Adrian Ratter, David Claridge, Jayen Ashar, Bernhard Hengst:
Fast Object Detection with Foveated Imaging and Virtual Saccades on Resource Limited Robots. Australasian Conference on Artificial Intelligence 2011: 560-569 - [c16]Bernhard Hengst, Manuel Lange, Brock White:
Learning ankle-tilt and foot-placement control for flat-footed bipedal balancing and walking. Humanoids 2011: 288-293 - [c15]Raymond Ka-Man Sheh, Bernhard Hengst, Claude Sammut:
Behavioural cloning for driving robots over rough terrain. IROS 2011: 732-737 - 2010
- [r1]Bernhard Hengst:
Hierarchical Reinforcement Learning. Encyclopedia of Machine Learning 2010: 495-502
2000 – 2009
- 2009
- [c14]Shihab Hamid, Bernhard Hengst:
Learning and Recognition of 3D Visual Objects in Real-Time. Australasian Conference on Artificial Intelligence 2009: 150-159 - [c13]Chen Cai, Bernhard Hengst, Getian Ye, Enyang Huang, Yang Wang, J. Carlos Aydos, Glenn Geers:
On the performance of adaptive traffic signal control. GIS-IWCTS 2009: 37-42 - [c12]J. Carlos Aydos, Bernhard Hengst, William Uther:
Kalman filter process models for urban vehicle tracking. ITSC 2009: 1-8 - 2008
- [c11]Bernhard Hengst:
Partial Order Hierarchical Reinforcement Learning. Australasian Conference on Artificial Intelligence 2008: 138-149 - 2007
- [c10]Bernhard Hengst:
Safe State Abstraction and Reusable Continuing Subtasks in Hierarchical Reinforcement Learning. Australian Conference on Artificial Intelligence 2007: 58-67 - 2005
- [c9]Robert Fitch, Bernhard Hengst, Dorian Suc, Greg Calbert, Jason B. Scholz:
Structural Abstraction Experiments in Reinforcement Learning. Australian Conference on Artificial Intelligence 2005: 164-175 - 2004
- [j1]Duncan Potts, Bernhard Hengst:
Discovering multiple levels of a task hierarchy concurrently. Robotics Auton. Syst. 49(1-2): 43-55 (2004) - [c8]Bernhard Hengst:
Model Approximation for HEXQ Hierarchical Reinforcement Learning. ECML 2004: 144-155 - 2003
- [b1]Bernhard Hengst:
Discovering hierarchy in reinforcement learning. University of New South Wales, Sydney, Australia, 2003 - 2002
- [c7]Bernhard Hengst:
Discovering Hierarchy in Reinforcement Learning with HEXQ. ICML 2002: 243-250 - 2001
- [c6]Claude Sammut, Bernhard Hengst:
The Evolution of a Robot Soccer Team. ISRR 2001: 517-530 - [c5]Spencer Chen, Martin Siu, Thomas Vogelgesang, Tak Fai Yik, Bernhard Hengst, Son Bao Pham, Claude Sammut:
The UNSW RoboCup 2001 Sony Legged Robot League Team. RoboCup 2001: 39-48 - [c4]Bernhard Hengst, Darren Ibbotson, Son Bao Pham, Claude Sammut:
Omnidirectional Locomotion for Quadruped Robots. RoboCup 2001: 368-373 - [c3]Son Bao Pham, Bernhard Hengst, Darren Ibbotson, Claude Sammut:
Stochastic Gradient Descent Localisation in Quadruped Robots. RoboCup 2001: 447-452 - 2000
- [c2]Bernhard Hengst:
Generating Hierarchical Structure in Reinforcement Learning from State Variables. PRICAI 2000: 533-543 - [c1]Bernhard Hengst, Darren Ibbotson, Son Bao Pham, John Dalgiesh, Mike Lawther, Phil Preston, Claude Sammut:
The UNSW RoboCup 2000 Sony Legged League Team. RoboCup 2000: 64-75
Coauthor Index
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