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ORCIDBenjamin Rosman
Benjamin Saul Rosman
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- affiliation: University of the Witwatersrand, Johannesburg, South Africa
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2020 – today
- 2024
[j14]Ofir Marom
, Benjamin Rosman:
Transferable dynamics models for efficient object-oriented reinforcement learning. Artif. Intell. 329: 104079 (2024)- [j13]Michael Beukman, Manuel Fokam, Marcel Kruger, Guy Axelrod, Muhammad Umair Nasir, Branden Ingram, Benjamin Rosman, Steven James:
Hierarchically Composing Level Generators for the Creation of Complex Structures. IEEE Trans. Games 16(2): 459-469 (2024) - [c46]Geraud Nangue Tasse, Devon Jarvis, Steven James, Benjamin Rosman:
Skill Machines: Temporal Logic Skill Composition in Reinforcement Learning. ICLR 2024 - [i34]Tristan Bester, Benjamin Rosman:
Towards Financially Inclusive Credit Products Through Financial Time Series Clustering. CoRR abs/2402.11066 (2024) - [i33]Perusha Moodley, Pramod Kaushik, Dhillu Thambi, Mark Trovinger, Praveen Paruchuri, Xia Hong, Benjamin Rosman:
Multi-State-Action Tokenisation in Decision Transformers for Multi-Discrete Action Spaces. CoRR abs/2407.01310 (2024) - [i32]Michael Beukman, Branden Ingram, Geraud Nangue Tasse, Benjamin Rosman, Pravesh Ranchod:
RobocupGym: A challenging continuous control benchmark in Robocup. CoRR abs/2407.14516 (2024) - [i31]Atnafu Lambebo Tonja, Bonaventure F. P. Dossou, Jessica Ojo, Jenalea Rajab, Fadel Thior, Eric Peter Wairagala, Aremu Anuoluwapo, Pelonomi Moiloa, Jade Abbott, Vukosi Marivate, Benjamin Rosman:
InkubaLM: A small language model for low-resource African languages. CoRR abs/2408.17024 (2024) - 2023
- [j12]Tamlin Love, Ritesh Ajoodha, Benjamin Rosman:
Who should I trust? Cautiously learning with unreliable experts. Neural Comput. Appl. 35(23): 16865-16875 (2023) - [j11]Branden Ingram, Clint J. van Alten, Richard Klein, Benjamin Rosman:
Generating Interpretable Play-Style Descriptions Through Deep Unsupervised Clustering of Trajectories. IEEE Trans. Games 15(4): 507-516 (2023) - [j10]O. Can Görür, Benjamin Rosman, Fikret Sivrikaya, Sahin Albayrak:
FABRIC: A Framework for the Design and Evaluation of Collaborative Robots with Extended Human Adaptation. ACM Trans. Hum. Robot Interact. 12(3): 38:1-38:54 (2023) - [c45]Michael Beukman, Branden Ingram, Ireton Liu, Benjamin Rosman:
Hierarchical WaveFunction Collapse. AIIDE 2023: 23-33 - [c44]Branden Ingram, Clint J. van Alten, Richard Klein, Benjamin Rosman:
Creating Diverse Play-Style-Centric Agents through Behavioural Cloning. AIIDE 2023: 255-265 - [c43]Siddarth Shandeep Singh, Benjamin Rosman:
The Challenge of Redundancy on Multi-agent Value Factorisation. AAMAS 2023: 2436-2438 - [c42]Devon Jarvis, Richard Klein, Benjamin Rosman, Andrew M. Saxe:
On The Specialization of Neural Modules. ICLR 2023 - [c41]Michael Beukman, Devon Jarvis, Richard Klein, Steven James, Benjamin Rosman:
Dynamics Generalisation in Reinforcement Learning via Adaptive Context-Aware Policies. NeurIPS 2023 - [i30]Michael Beukman, Manuel Fokam, Marcel Kruger, Guy Axelrod, Muhammad Umair Nasir, Branden Ingram, Benjamin Rosman, Steven James:
Hierarchically Composing Level Generators for the Creation of Complex Structures. CoRR abs/2302.01561 (2023) - [i29]Siddarth Singh, Benjamin Rosman:
The challenge of redundancy on multi-agent value factorisation. CoRR abs/2304.00009 (2023) - [i28]Geraud Nangue Tasse, Tamlin Love, Mark Nemecek, Steven James, Benjamin Rosman:
ROSARL: Reward-Only Safe Reinforcement Learning. CoRR abs/2306.00035 (2023) - [i27]Rowan Hodson, Bruce Bassett, Charel van Hoof, Benjamin Rosman, Mark Solms, Jonathan P. Shock, Ryan Smith:
Planning to Learn: A Novel Algorithm for Active Learning during Model-Based Planning. CoRR abs/2308.08029 (2023) - [i26]Michael Beukman, Devon Jarvis, Richard Klein, Steven James, Benjamin Rosman:
Dynamics Generalisation in Reinforcement Learning via Adaptive Context-Aware Policies. CoRR abs/2310.16686 (2023) - [i25]Kale-ab Tessera, Callum Rhys Tilbury, Sasha Abramowitz, Ruan de Kock, Omayma Mahjoub, Benjamin Rosman, Sara Hooker, Arnu Pretorius:
Generalisable Agents for Neural Network Optimisation. CoRR abs/2311.18598 (2023) - [i24]Tristan Bester, Benjamin Rosman, Steven James, Geraud Nangue Tasse:
Counting Reward Automata: Sample Efficient Reinforcement Learning Through the Exploitation of Reward Function Structure. CoRR abs/2312.11364 (2023) - 2022
- [c40]Herkulaas MvE Combrink, Vukosi Marivate, Benjamin Rosman:
Reinforcement Learning in Education: A Multi-armed Bandit Approach. AFRICATEK 2022: 3-16 - [c39]Branden Ingram, Benjamin Rosman, Clint J. van Alten, Richard Klein:
Play-style Identification through Deep Unsupervised Clustering of Trajectories. CoG 2022: 393-400 - [c38]Branden Ingram, Benjamin Rosman, Clint J. van Alten, Richard Klein:
Improved Action Prediction through Multiple Model Processing of Player Trajectories. CoG 2022: 548-551 - [c37]Steven James, Benjamin Rosman, George Konidaris:
Autonomous Learning of Object-Centric Abstractions for High-Level Planning. ICLR 2022 - [c36]Geraud Nangue Tasse, Steven James, Benjamin Rosman:
Generalisation in Lifelong Reinforcement Learning through Logical Composition. ICLR 2022 - [c35]Logan Dunbar, Benjamin Rosman, Anthony G. Cohn, Matteo Leonetti:
Reducing the Planning Horizon Through Reinforcement Learning. ECML/PKDD (4) 2022: 68-83 - [c34]Lindsay John Arendse, Branden Ingram, Benjamin Rosman:
Real Time In-Game Playstyle Classification Using a Hybrid Probabilistic Supervised Learning Approach. SACAIR 2022: 60-77 - [i23]Steven James, Benjamin Rosman, George Dimitri Konidaris:
Learning Abstract and Transferable Representations for Planning. CoRR abs/2205.02092 (2022) - [i22]Geraud Nangue Tasse, Steven James, Benjamin Rosman:
World Value Functions: Knowledge Representation for Multitask Reinforcement Learning. CoRR abs/2205.08827 (2022) - [i21]Geraud Nangue Tasse, Devon Jarvis, Steven James, Benjamin Rosman:
Skill Machines: Temporal Logic Composition in Reinforcement Learning. CoRR abs/2205.12532 (2022) - [i20]Geraud Nangue Tasse, Benjamin Rosman, Steven James:
World Value Functions: Knowledge Representation for Learning and Planning. CoRR abs/2206.11940 (2022) - [i19]Herkulaas MvE Combrink, Vukosi Marivate, Benjamin Rosman:
Comparing Synthetic Tabular Data Generation Between a Probabilistic Model and a Deep Learning Model for Education Use Cases. CoRR abs/2210.08528 (2022) - [i18]Herkulaas MvE Combrink, Vukosi Marivate, Benjamin Rosman:
A Framework for Undergraduate Data Collection Strategies for Student Support Recommendation Systems in Higher Education. CoRR abs/2210.10657 (2022) - [i17]Herkulaas Combrink, Vukosi Marivate, Benjamin Rosman:
Reinforcement Learning in Education: A Multi-Armed Bandit Approach. CoRR abs/2211.00779 (2022) - 2021
- [j9]Mary Carman, Benjamin Rosman:
Applying a principle of explicability to AI research in Africa: should we do it? Ethics Inf. Technol. 23(2): 107-117 (2021) - [j8]Caroline M. Gevaert, Mary Carman, Benjamin Rosman, Yola Georgiadou, Robert Soden:
Fairness and accountability of AI in disaster risk management: Opportunities and challenges. Patterns 2(11): 100363 (2021) - [i16]Kale-ab Tessera, Sara Hooker, Benjamin Rosman:
Keep the Gradients Flowing: Using Gradient Flow to Study Sparse Network Optimization. CoRR abs/2102.01670 (2021) - [i15]O. Can Görür, Benjamin Rosman, Fikret Sivrikaya, Sahin Albayrak:
FABRIC: A Framework for the Design and Evaluation of Collaborative Robots with Extended Human Adaptation. CoRR abs/2104.01976 (2021) - [i14]Vanya Cohen, Geraud Nangue Tasse, Nakul Gopalan, Steven James, Matthew C. Gombolay, Benjamin Rosman:
Learning to Follow Language Instructions with Compositional Policies. CoRR abs/2110.04647 (2021) - 2020
- [j7]Arnu Pretorius, Elan Van Biljon, Benjamin van Niekerk, Ryan Eloff, Matthew Reynard, Steven James, Benjamin Rosman, Herman Kamper, Steve Kroon:
If dropout limits trainable depth, does critical initialisation still matter? A large-scale statistical analysis on ReLU networks. Pattern Recognit. Lett. 138: 95-105 (2020) - [j6]Geethen Singh, Chevonne Reynolds, Marcus Byrne, Benjamin Rosman:
A Remote Sensing Method to Monitor Water, Aquatic Vegetation, and Invasive Water Hyacinth at National Extents. Remote. Sens. 12(24): 4021 (2020) - [c33]Ofir Marom, Benjamin Rosman:
Utilising Uncertainty for Efficient Learning of Likely-Admissible Heuristics. ICAPS 2020: 560-568 - [c32]Steven James, Benjamin Rosman, George Konidaris:
Learning Portable Representations for High-Level Planning. ICML 2020: 4682-4691 - [c31]Geraud Nangue Tasse, Steven James, Benjamin Rosman:
A Boolean Task Algebra for Reinforcement Learning. NeurIPS 2020 - [i13]Geraud Nangue Tasse, Steven James, Benjamin Rosman:
A Boolean Task Algebra for Reinforcement Learning. CoRR abs/2001.01394 (2020) - [i12]Benjamin van Niekerk, Andreas C. Damianou, Benjamin Rosman:
Online Constrained Model-based Reinforcement Learning. CoRR abs/2004.03499 (2020)
2010 – 2019
- 2019
- [j5]Tadahiro Taniguchi, Justus H. Piater, Florentin Wörgötter, Emre Ugur, Matej Hoffmann, Lorenzo Jamone, Takayuki Nagai, Benjamin Rosman, Toshihiko Matsuka, Naoto Iwahashi, Erhan Öztop:
Symbol Emergence in Cognitive Developmental Systems: A Survey. IEEE Trans. Cogn. Dev. Syst. 11(4): 494-516 (2019) - [c30]O. Can Görür, Benjamin Rosman, Sahin Albayrak:
Anticipatory Bayesian Policy Selection for Online Adaptation of Collaborative Robots to Unknown Human Types. AAMAS 2019: 77-85 - [c29]Benjamin van Niekerk, Steven James, Adam Christopher Earle, Benjamin Rosman:
Composing Value Functions in Reinforcement Learning. ICML 2019: 6401-6409 - [c28]Perusha Moodley, Benjamin Rosman, Xia Hong:
Understanding Structure of Concurrent Actions. SGAI Conf. 2019: 78-90 - [i11]Montaser Mohammedalamen, Waleed D. Khamies, Benjamin Rosman:
Transfer Learning for Prosthetics Using Imitation Learning. CoRR abs/1901.04772 (2019) - [i10]Steven James, Benjamin Rosman, George Dimitri Konidaris:
Learning Portable Representations for High-Level Planning. CoRR abs/1905.12006 (2019) - [i9]Adam Pantanowitz, Emmanuel Cohen, Philippe Gradidge, Nigel Crowther, Vered Aharonson, Benjamin Rosman, David M. Rubin:
Estimation of Body Mass Index from Photographs using Deep Convolutional Neural Networks. CoRR abs/1908.11694 (2019) - [i8]Arnu Pretorius, Elan Van Biljon, Benjamin van Niekerk, Ryan Eloff, Matthew Reynard, Steven James, Benjamin Rosman, Herman Kamper, Steve Kroon:
If dropout limits trainable depth, does critical initialisation still matter? A large-scale statistical analysis on ReLU networks. CoRR abs/1910.05725 (2019) - 2018
- [j4]Ndivhuwo Makondo, Michihisa Hiratsuka, Benjamin Rosman, Osamu Hasegawa:
A Non-Linear Manifold Alignment Approach to Robot Learning from Demonstrations. J. Robotics Mechatronics 30(2): 265-281 (2018) - [c27]Ritesh Ajoodha, Benjamin Rosman:
Learning the Influence Structure between Partially Observed Stochastic Processes Using IoT Sensor Data. AAAI Workshops 2018: 167-173 - [c26]Ofir Marom, Benjamin Rosman:
Belief Reward Shaping in Reinforcement Learning. AAAI 2018: 3762-3769 - [c25]Abdallah M. Bashir, Abubakr Hassan, Benjamin Rosman, Daniel Duma, Mohanad Ahmed:
Implementation of A Neural Natural Language Understanding Component for Arabic Dialogue Systems. ACLING 2018: 222-229 - [c24]O. Can Görür, Benjamin Rosman, Fikret Sivrikaya, Sahin Albayrak:
Social Cobots: Anticipatory Decision-Making for Collaborative Robots Incorporating Unexpected Human Behaviors. HRI 2018: 398-406 - [c23]Adam Christopher Earle, Andrew M. Saxe, Benjamin Rosman:
Hierarchical Subtask Discovery with Non-Negative Matrix Factorization. ICLR (Poster) 2018 - [c22]Ndivhuwo Makondo, Benjamin Rosman, Osamu Hasegawa:
Accelerating Model Learning with Inter-Robot Knowledge Transfer. ICRA 2018: 2417-2424 - [c21]Richard Fisher, Benjamin Rosman, Vladimir Ivan:
Real-Time Motion Planning in Changing Environments Using Topology-Based Encoding of Past Knowledge. IROS 2018: 6512-6517 - [c20]Ofir Marom, Benjamin Rosman:
Zero-Shot Transfer with Deictic Object-Oriented Representation in Reinforcement Learning. NeurIPS 2018: 2297-2305 - [i7]Craig Innes, Alex Lascarides, Stefano V. Albrecht, Subramanian Ramamoorthy, Benjamin Rosman:
Reasoning about Unforeseen Possibilities During Policy Learning. CoRR abs/1801.03331 (2018) - [i6]Tadahiro Taniguchi, Emre Ugur, Matej Hoffmann, Lorenzo Jamone, Takayuki Nagai, Benjamin Rosman, Toshihiko Matsuka, Naoto Iwahashi, Erhan Öztop, Justus H. Piater, Florentin Wörgötter:
Symbol Emergence in Cognitive Developmental Systems: a Survey. CoRR abs/1801.08829 (2018) - [i5]Benjamin van Niekerk, Steven James, Adam Christopher Earle, Benjamin Rosman:
Will it Blend? Composing Value Functions in Reinforcement Learning. CoRR abs/1807.04439 (2018) - 2017
- [c19]Steven James, George Dimitri Konidaris, Benjamin Rosman:
An Analysis of Monte Carlo Tree Search. AAAI 2017: 3576-3582 - [c18]Luke Nicholas Darlow, Benjamin Rosman:
Fingerprint minutiae extraction using deep learning. IJCB 2017: 22-30 - [c17]Andrew M. Saxe, Adam Christopher Earle, Benjamin Rosman:
Hierarchy Through Composition with Multitask LMDPs. ICML 2017: 3017-3026 - [c16]Benjamin van Niekerk, Andreas C. Damianou, Benjamin Rosman:
Online Constrained Model-based Reinforcement Learning. UAI 2017 - [i4]Adam Christopher Earle, Andrew M. Saxe, Benjamin Rosman:
Hierarchical Subtask Discovery With Non-Negative Matrix Factorization. CoRR abs/1708.00463 (2017) - 2016
- [j3]Benjamin Rosman, Majd Hawasly, Subramanian Ramamoorthy:
Bayesian policy reuse. Mach. Learn. 104(1): 99-127 (2016) - [c15]Pablo Hernandez-Leal, Matthew E. Taylor, Benjamin Rosman, Luis Enrique Sucar, Enrique Munoz de Cote:
Identifying and Tracking Switching, Non-Stationary Opponents: A Bayesian Approach. AAAI Workshop: Multiagent Interaction without Prior Coordination 2016 - [c14]Pablo Hernandez-Leal, Benjamin Rosman, Matthew E. Taylor, Luis Enrique Sucar, Enrique Munoz de Cote:
A Bayesian Approach for Learning and Tracking Switching, Non-Stationary Opponents: (Extended Abstract). AAMAS 2016: 1315-1316 - [c13]Michihisa Hiratsuka, Ndivhuwo Makondo, Benjamin Rosman, Osamu Hasegawa:
Trajectory learning from human demonstrations via manifold mapping. IROS 2016: 3935-3940 - [i3]Andrew M. Saxe, Adam Christopher Earle, Benjamin Rosman:
Hierarchy through Composition with Linearly Solvable Markov Decision Processes. CoRR abs/1612.02757 (2016) - 2015
- [j2]Benjamin Rosman, Subramanian Ramamoorthy:
Action Priors for Learning Domain Invariances. IEEE Trans. Auton. Ment. Dev. 7(2): 107-118 (2015) - [c12]Ndivhuwo Makondo, Benjamin Rosman, Osamu Hasegawa:
Knowledge transfer for learning robot models via Local Procrustes Analysis. Humanoids 2015: 1075-1082 - [c11]Benjamin Rosman, Bradley Hayes, Brian Scassellati:
Enhancing agent safety through autonomous environment adaptation. ICDL-EPIROB 2015: 214-219 - [c10]Pravesh Ranchod, Benjamin Rosman, George Dimitri Konidaris:
Nonparametric Bayesian reward segmentation for skill discovery using inverse reinforcement learning. IROS 2015: 471-477 - [i2]Benjamin Rosman, Majd Hawasly, Subramanian Ramamoorthy:
Bayesian Policy Reuse. CoRR abs/1505.00284 (2015) - 2014
- [c9]Benjamin Saul Rosman:
Behavioural Domain Knowledge Transfer for Autonomous Agents. AAAI Fall Symposia 2014 - [c8]Ashley Kleinhans, Serge Thill, Benjamin Rosman, Renaud Detry, Bryan P. Tripp:
Modelling Primate Control of Grasping for Robotics Applications. ECCV Workshops (2) 2014: 438-447 - [c7]Benjamin Rosman:
Feature selection for domain knowledge representation through multitask learning. ICDL-EPIROB 2014: 216-221 - [c6]Benjamin Rosman, Subramanian Ramamoorthy:
Giving advice to agents with hidden goals. ICRA 2014: 1959-1964 - [c5]Benjamin Rosman, Subramanian Ramamoorthy, M. M. Hassan Mahmud, Pushmeet Kohli:
On user behaviour adaptation under interface change. IUI 2014: 273-278 - 2013
- [i1]M. M. Hassan Mahmud, Majd Hawasly, Benjamin Rosman, Subramanian Ramamoorthy:
Clustering Markov Decision Processes For Continual Transfer. CoRR abs/1311.3959 (2013) - 2012
- [c4]Benjamin Saul Rosman, Subramanian Ramamoorthy:
A Multitask Representation Using Reusable Local Policy Templates. AAAI Spring Symposium: Designing Intelligent Robots 2012 - [c3]Benjamin Rosman, Subramanian Ramamoorthy:
What good are actions? Accelerating learning using learned action priors. ICDL-EPIROB 2012: 1-6 - 2011
- [j1]Benjamin Rosman, Subramanian Ramamoorthy:
Learning spatial relationships between objects. Int. J. Robotics Res. 30(11): 1328-1342 (2011) - 2010
- [c2]Benjamin Rosman, Subramanian Ramamoorthy:
A game-theoretic procedure for learning hierarchically structured strategies. ICRA 2010: 2977-2983
2000 – 2009
- 2006
- [c1]Sarah Rauchas, Benjamin Rosman, George Dimitri Konidaris, Ian D. Sanders:
Language performance at high school and success in first year computer science. SIGCSE 2006: 398-402
Coauthor Index
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