2023
| 1. N. Michlo, R. Klein, S. James Overlooked implications of the reconstruction loss for VAE disentanglement. Proceedings of the Thirty-second International Joint Conference on Artificial Intelligence, August 2023. |
| 2. D. Jarvis, V. Klar, R. Klein, B. Rosman, A. Saxe. Revisiting the Role of Relearning in Semantic Dementia. Conference on Cognitive Computational Neuroscience, August 2023. |
| 3. M. Nasir, M. Beukman, S. James, C. Cleghorn. Augmentative Topology Agents for Open-ended Learning. Genetic and Evolutionary Computation Conference, July 2023. |
| 4. D. Jarvis, R. Klein, B. Rosman, A. Saxe. On The Specialization of Neural Modules. Proceedings of the Eleventh International Conference on Learning Representations, May 2023. |
| 5. S. Singh, B. Rosman. The Challenge of Redundancy on Multi-agent Value Factorisation. International Conference on Autonomous Agents and Multiagent Systems, May 2023. [Extended Abstract] |
| 6. R. Lastrucci, I. Dzingirai, J. Rajab, A. Madodonga, M. Shingange, D. Njini, V. Marivate. Preparing the Vuk’uzenzele and ZA-gov-multilingual South African multilingual corpora. Workshop on Resources for African Indigenous Language (RAIL) @ EACL, May 2023. |
| 7. C. Currin, M. Asiedu, C. Fourie, B. Rosman, H. Turki, A. Tonja, J. Abbott, M. Ajala, S. Adedayo, C. Emezue, D. Machangara. A Framework for Grassroots Research Collaboration in Machine Learning and Global Health. ICLR Workshop on Machine Learning & Global Health, May 2023. |
| 8. O. Can Görür , B. Rosman , F. Sivrikaya , S. Albayrak. FABRIC: A Framework for the Design and Evaluation of Collaborative Robots with Extended Human Adaptation. ACM Transactions on Human-Robot Interaction, March 2023. |
2022
| 1. V. Cohen*, G. Nangue Tasse*, N. Gopalan, S. James, R. Mooney, B. Rosman. End-to-End Learning to Follow Language Instructions with Compositional Policies. Workshop on Language and Robot Learning @ CORL, December 2022. |
| 2. L.J. Arendse, B. Ingram, B. Rosman. Real Time In-Game Playstyle Classification Using A Hybrid Probabilistic Supervised Learning Approach. The Third Southern African Conference for AI Research Proceedings. Part of the book series: Communications in Computer and Information Science, Springer, December 2022. |
| 3. H. Combrink, V. Marivate, B. Rosman. Reinforcement Learning in Education: A Multi-Armed Bandit Approach. 5th EAI International Conference on Emerging Technologies for Developing Countries, December 2022. |
| 4. W. Onyothi Nekoto, J. Kreutzer, J. Rajab, M. Ochieng, J. Abbott. Participatory Translations of Oshiwambo: Towards Culture Preservation with Language Technology. Workshop on NLP for Positive Impact @ EMNLP, December 2022. |
| 5. H. Combrink, V. Marivate, B. Rosman. Comparing Synthetic Tabular Data Generation Between a Probabilistic Model and a Deep Learning Model for Education Use Cases. The Third Southern African Conference for AI Research Proceedings, December 2022. |
| 6. G. Crafford, B. Rosman. Improving Reinforcement Learning with Ensembles of Different Learners. RAPDASA/ROBMECH/PRASA/CoSAAMI International Conference, November 2022. |
| 7. G. Nangue Tasse, D. Jarvis, S. James, B. Rosman. Skill Machines: Temporal Logic Composition in Reinforcement Learning. Lifelong Learning of High-level Cognitive and Reasoning Skills Workshop @ IROS, October 2022. |
| 8. M. Nasir, M. Beukman, S. James, C. Cleghorn. Augmentative Topology Agents For Open-ended Learning. Lifelong Learning of High-level Cognitive and Reasoning Skills Workshop @ IROS, October 2022. |
| 9. T. Love*, D. Jarvis*, G. Nangue Tasse*, B. Ingram, S. James, B. Rosman. Facilitating Safe Sim-to-Real through Simulator Abstraction and Zero-shot Task Composition. Lifelong Learning of High-level Cognitive and Reasoning Skills Workshop @ IROS, October 2022. |
| 10. T. Love, R. Ajoodha, B. Rosman. Who should I trust? Cautiously learning with unreliable experts. Neural Computing and Applications, September 2022. |
| 11. L. Dunbar, B. Rosman, A. Cohn, M. Leonetti. Reducing the Planning Horizon through Reinforcement Learning. Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, September 2022. |
| 12. B. Ingram, B. Rosman, C. van Alten, R. Klein. Play-style Identification through Deep Unsupervised Clustering of Trajectories. Proceedings of the IEEE Conference on Games, August 2022. [Best Paper Nominee] |
| 13. B. Ingram, B. Rosman, C. van Alten, R. Klein. Improved Action Prediction through Multiple Model Processing of Player Trajectories. Proceedings of the IEEE Conference on Games, August 2022. |
| 14. K. Tessera, C. Matowe, A. Pretorius, B. Rosman, S. Hooker. Just-in-Time Sparsity: Learning Dynamic Sparsity Schedules. Workshop on Dynamic Neural Networks @ ICML, July 2022. |
| 15. M. Beukman, C. Cleghorn, S. James. Procedural Content Generation using Neuroevolution and Novelty Search for Diverse Video Game Levels. Proceedings of the Genetic and Evolutionary Computation Conference, July 2022. |
| 16. M. Vogt, B. Rosman. Analyzing Reinforcement Learning Algorithms for Nitrogen Fertilizer Management in Simulated Crop Growth. Proceedings of 43rd Conference of the South African Institute of Computer Scientists and Information Technologists, July 2022. [Best Paper Award] |
| 17. N. Muir, S. James. Combining Evolutionary Search with Behaviour Cloning for Procedurally Generated Content. Proceedings of 43rd Conference of the South African Institute of Computer Scientists and Information Technologists, July 2022. |
| 18. G. Nangue Tasse, D. Jarvis, S. James, B. Rosman. Skill Machines: Temporal Logic Composition in Reinforcement Learning. Technical Report, June 2022. |
| 19. T. Love, R. Ajoodha, B. Rosman. Harnessing the Wisdom of an Unreliable Crowd for Autonomous Decision Making. The Multi-disciplinary Conference on Reinforcement Learning and Decision Making, June 2022. [Extended Abstract] |
| 20. M. Beukman, M. Mitchley, D. Wookey, S. James, G. Konidaris. Adaptive Online Value Function Approximation with Wavelets. The Multi-disciplinary Conference on Reinforcement Learning and Decision Making, June 2022. [Extended Abstract] |
| 21. N. Michlo, D. Jarvis, R. Klein, S. James. Accounting for the Sequential Nature of States to Learn Representations in Reinforcement Learning. The Multi-disciplinary Conference on Reinforcement Learning and Decision Making, June 2022. [Extended Abstract] |
| 22. S. James, B. Rosman, G. Konidaris. Learning Abstract and Transferable Representations for Planning. The Multi-disciplinary Conference on Reinforcement Learning and Decision Making, June 2022. [Extended Abstract] |
| 23. J.J. Shipton, B. Rosman. Diverse Partner Creation with Partner Prediction for Robust K-Level Reasoning. The Multi-disciplinary Conference on Reinforcement Learning and Decision Making, June 2022. [Extended Abstract] |
| 24. G. Nangue Tasse, S. James, B. Rosman. World Value Functions: Knowledge Representation for Multitask Reinforcement Learning. The Multi-disciplinary Conference on Reinforcement Learning and Decision Making, June 2022. [Extended Abstract] |
| 25. G. Nangue Tasse, S. James, B. Rosman. Generalisation in Lifelong Reinforcement Learning through Logical Composition. Proceedings of the Tenth International Conference on Learning Representations, April 2022. |
| 26. S. James, B. Rosman, G. Konidaris. Autonomous Learning of Object-Centric Abstractions for High-Level Planning. Proceedings of the Tenth International Conference on Learning Representations, April 2022. |
| 27. M. Beukman. Analysing the Effects of Transfer Learning on Low-Resourced Named Entity Recognition Performance. 3rd Workshop on African Natural Language Processing, April 2022. |
| 28. J. Rajab. Effect of Tokenisation Strategies for Low-Resourced Southern African Languages. 3rd Workshop on African Natural Language Processing, April 2022. |
| 29. N. Kooverjee, S. James, T. van Zyl. Investigating Transfer Learning in Graph Neural Networks. Electronics, April 2022. |
2021
| 1. S. Singh, B. Rosman. The Challenge of Redundancy on Multi-Agent Value Factorisation. NeurIPS Workshop on Cooperative AI, December 2021. |
| 2. G. Nangue Tasse, S. James, B. Rosman. Generalisation in Lifelong Reinforcement Learning through Logical Composition. NeurIPS Deep Reinforcement Learning Workshop, December 2021. |
| 3. R. Sefala, T. Gebru, N. Moorosi, R. Klein. Constructing a Visual Dataset to Study the Effects of Spatial Apartheid in South Africa. NeurIPS 2021 Datasets and Benchmarks Track, December 2021. |
| 4. D. Poulton, R. Klein. Improving Pose Estimation through Contextual Activity Fusion. Southern African Conference for Artificial Intelligence Research, December 2021. |
| 5. R. Ajoodha, B. Rosman. Using Score-based Structure Learning to Computationally Learn Direct Influence between Hierarchical Dynamic Bayesian Networks. IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE), December 2021. |
| 6. C. Gevaert, M. Carman, B. Rosman, Y. Georgiadou, R. Soden. Fairness and accountability of AI in disaster risk management: Opportunities and challenges. Patterns (Elsevier), November 2021. |
| 7. J. Harris-Dewey, R. Klein. Generative Adversarial Networks for Global Illumination and Indirect Lighting as a Replacement for Ray-tracing in Older GPU Hardware. International Conference in Soft Computing and Machine Intelligence, November 2021. |
| 8. V. Cohen*, G. Nangue Tasse*, N. Gopalan, S. James, M. Gombolay, B. Rosman. Learning to Follow Language Instructions with Compositional Policies. AAAI Fall Symposium on AI for Human-Robot Interaction, November 2021. |
| 9. A. Pantanowitz, E.Cohen, P. Gradidge, N. Crowther, V. Aharonson, B. Rosman, D. Rubin. Estimation of Body Mass Index from photographs using deep Convolutional Neural Networks. Informatics in Medicine Unlocked, September 2021. |
| 10. A. Pantanowitz, B. Rosman, N. Crowther, D. Rubin. The Hospital as a Sorting Machine. Informatics in Medicine Unlocked, August 2021. |
| 11. T. Love, R. Ajoodha, B. Rosman. Should I Trust You? Incorporating Unreliable Expert Advice in Human-Agent Interaction. Workshop on Human-aligned Reinforcement Learning for Autonomous Agents and Robots at ICDL, August 2021. |
| 12. K. Tessera, S. Hooker, B. Rosman. Keep the Gradients Flowing: Using Gradient Flow to Study Sparse Network Optimization. Sparsity in Neural Networks: Advancing Understanding and Practice, July 2021. |
| 13. L. Pratt, D. Govender, R. Klein. Defect Detection and Quantification in Electroluminescence Images of Solar PV Modules using U-net Semantic Segmentation. Renewable Energy, June 2021. |
| 14. M. Saeed, M. Nagdi, B. Rosman, H. Ali. Deep Reinforcement Learning for Robotic Hand Manipulation. International Conference on Computer, Control, Electrical, and Electronics Engineering, February 2021. |
| 15. M. Omer, R. Ahmed, B. Rosman, S. Babikir. Model Predictive-Actor Critic Reinforcement Learning for Dexterous Manipulation. International Conference on Computer, Control, Electrical, and Electronics Engineering, February 2021. |
| 16. H. Combrink, V. Marivate, B. Rosman. A Framework for Undergraduate Data Collection Strategies for Student Support Recommendation Systems in Higher Education. Southern African Conference for Artificial Intelligence Research, February 2021. |
| 17. T. Boloka, N. Makondo, B. Rosman. Knowledge Transfer using Model-Based Deep Reinforcement Learning. SAUPEC/ROBMECH/PRASA International Conference, January 2021. |
2020
| 1. G. Nangue Tasse, S. James, B. Rosman. A Boolean Task Algebra for Reinforcement Learning. Advances in Neural Information Processing Systems (NeurIPS), December 2020. |
| 2. G. Singh, C. Reynolds, M. Byrne, B. Rosman. A Remote Sensing Method to Monitor Water, Aquatic Vegetation, and Invasive Water Hyacinth at National Extents. Remote Sensing 2020, 12(24), 4021. |
| 3. O. Marom, B. Rosman. Utilising Uncertainty for Efficient Learning of Likely-Admissible Heuristics. International Conference on Automated Planning and Scheduling (ICAPS), October 2020. [Supplementary Material] |
| 4. R. Ajoodha, B. Rosman. Learning the Influence between Partially Observable Processes using Score- based Structure Learning. Advances in Science, Technology and Engineering Systems Journal, Volume 5(5) 2020. |
| 5. R. Ajoodha, B. Rosman. Discovery of Influence between Processes Represented by Hidden Markov Models. International IOT, Electronics and Mechatronics Conference (IEMTRONICS), September 2020. |
| 6. S. James, B. Rosman, G. Konidaris. Learning Portable Representations for High-Level Planning. International Conference on Machine Learning, July 2020. |
| 7. S. James, B. Rosman, G. Konidaris. Learning Object-Centric Representations for High-Level Planning in Minecraft. Object-Oriented Learning (OOL): Perception, Representation, and Reasoning. Workshop at ICML, July 2020. |
| 8. G. Nangue Tasse, S. James, B. Rosman. Logical Composition for Lifelong Reinforcement Learning. 4th Lifelong Learning Workshop at ICML, July 2020. |
| 9. A. Pretorius, E. van Biljon, B. van Niekerk, R. Eloff, M. Reynard, S. James, B. Rosman, H. Kamper, S. Kroon. If dropout limits trainable depth, does critical initialisation still matter? A large-scale statistical analysis on ReLU networks. Pattern Recognition Letters, Elsevier, June 2020. |
| 10. M. Carman, B. Rosman. Applying a principle of explicability to AI research in Africa: should we do it? Ethics and Information Technology, 2020. |
| 11. G. Nangue Tasse, S. James, B. Rosman. A Boolean Task Algebra for Reinforcement Learning. Beyond “Tabula Rasa” in Reinforcement Learning (BeTR-RL): Agents that remember, adapt, and generalize (Workshop at ICLR), April 2020. |
| 12. M. Cockcroft, S. Mawjee, S. James, P. Ranchod. Learning Options from Demonstration using Skill Segmentation. SAUPEC/ROBMECH/PRASA International Conference, January 2020. |
| 13. N. Kooverjee, S. James, T. van Zyl. Inter-and Intra-domain Knowledge Transfer for Related Tasks in Deep Character Recognition. SAUPEC/ROBMECH/PRASA International Conference, January 2020. |
| 14. K. Paupamah, S. James, R. Klein. Quantisation and Pruning for Neural Network Compression and Regularisation. SAUPEC/ROBMECH/PRASA International Conference, January 2020. |
| 15. M. Reynard, H. Engelbrecht, H. Kamper, B. Rosman. Combining primitive DQNs for improved reinforcement learning in Minecraft. SAUPEC/ROBMECH/PRASA International Conference, January 2020. |
| 16. P. Burke, R. Klein. Confident in the Crowd: Bayesian Inference to Improve Data Labelling in Crowdsourcing. SAUPEC/ROBMECH/PRASA International Conference, January 2020. |
| 17. J. Oyasor, M. Raborife and P. Ranchod. Sentiment Analysis as an Indicator to Evaluate Gender disparity on Sexual Violence Tweets in South Africa. SAUPEC/ROBMECH/PRASA International Conference, January 2020. |
2019
| 1. E. Boje, R.L. Christopher, J. Fernandes, J.H. Hepworth, R.B. Kuriakose, K. Kruger, T. Lorimer, N. Luwes, H.D. Mouton, A. Patel, B. Rosman, W.J. Smit, R. Stopforth, B. van Eden, T. van Niekerk, H. Vermaak, D. Withey. A Review of Robotics Research in South Africa. R&D Journal, 35:75-97, 2019. |
| 2. P. Moodley, B. Rosman, X. Hong. Understanding Structure of Concurrent Actions. AI-2019: The Thirty-ninth SGAI International Conference, December 2019. |
| 3. B. van Niekerk*, S. James*, A. Earle, B. Rosman. Composing Value Functions in Reinforcement Learning. International Conference on Machine Learning, June 2019. [Supplementary Material] |
| 4. O.C. Görür, B. Rosman, S. Albayrak. Anticipatory Bayesian Policy Selection for Online Adaptation of Collaborative Robots to Unknown Human Types. International Conference on Autonomous Agents and Multiagent Systems, May 2019. |
| 5. C. Bester, S. James, G. Konidaris. Multi-Pass Q-Networks for Deep Reinforcement Learning with Parameterised Action Spaces. Technical Report, May 2019. |
| 6. D. Bhugwan, P. Ranchod, R. Klein, B. Rosman. A comparison between fully connected and deconvolutional layers for road segmentation from satellite imagery. SAUPEC/ROBMECH/PRASA International Conference, January 2019. |
| 7. N. Makondo, B. Rosman. Towards improving incremental learning of manipulator kinematics with inter-robot knowledge transfer. SAUPEC/ROBMECH/PRASA International Conference, January 2019. |
| 8. B. van Eden, B. Rosman. An overview of robot vision. SAUPEC/ROBMECH/PRASA International Conference, January 2019. |
2018
| 1. O. Marom, B. Rosman. Zero-Shot Transfer with Deictic Object-Oriented Representation in Reinforcement Learning. Advances in Neural Information Processing Systems (NeurIPS), December 2018. [Supplementary Material] |
| 2. A. Bashir, A. Hassan, B. Rosman, D. Duma, M Ahmed. Implementation of A Neural Natural Language Understanding Component for Arabic Dialogue Systems. The 4th International Conference on Arabic Computational Linguistics (ACLing), November 2018. |
| 3. R. Fisher, B. Rosman, V. Ivan. Real-time Motion Planning in Changing Environments Using Topology-based Encoding of Past Knowledge. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 2018. |
| 4. B. van Niekerk, S. James, A. Earle, B. Rosman. Will it Blend? Composing Value Functions in Reinforcement Learning. The 2nd Lifelong Learning: A Reinforcement Learning Approach (LLARLA) Workshop @ FAIM, July 2018. |
| 5. S. James, B. Rosman, G. Konidaris. Learning to Plan with Portable Symbols. ICML/IJCAI/AAMAS 2018 Workshop on Planning and Learning, July 2018. |
| 6. N. Makondo, B. Rosman, O. Hasegawa. Accelerating model learning with inter-robot knowledge transfer. IEEE International Conference on Robotics and Automation, May 2018. |
| 7. A. Earle, A. Saxe, B. Rosman. Hierarchical Subtask Discovery with Non-Negative Matrix Factorization. Proceedings of the Sixth International Conference on Learning Representations, April 2018. |
| 8. N. Makondo, M. Hiratsuka, B. Rosman, O. Hasegawa. A Non-linear Manifold Alignment Approach to Robot Learning from Demonstrations. Journal of Robotics and Mechatronics 30(2), April 2018. |
| 9. O.C. Görür, B. Rosman, F. Sivrikaya, S. Albayrak. Social Cobots: Anticipatory Decision-Making for Collaborative Robots Incorporating Unexpected Human Behaviors. ACM/IEEE International Conference on Human-Robot Interaction, March 2018. |
| 10. R. Ajoodha, B. Rosman. Learning the Influence Structure between Partially Observed Stochastic Processes using IoT Sensor Data. SmartIoT: AI Enhanced IoT Data Processing for Intelligent Applications at AAAI-18, February 2018. |
| 11. O. Marom, B. Rosman. Bayesian Reward Shaping in Reinforcement Learning. Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, February 2018. [Supplementary Material] |
| 12. T. Taniguchi, E. Ugur, M. Hoffmann, L. Jamone, T. Nagai, B. Rosman, T. Matsuka, N. Iwahashi, E. Oztop, J. Piater, F. Worgotter. Symbol Emergence in Cognitive Developmental Systems: a Survey. IEEE transactions on Cognitive and Developmental Systems, January 2018. |
| 13. C. Innes, A. Lascarides, S.V. Albrecht, S. Ramamoorthy, B. Rosman. Reasoning about Unforeseen Possibilities During Policy Learning. Technical Report, January 2018. |
2017
| 1. R. Ajoodha, B. Rosman. Tracking Influence between Naïve Bayes Models using Score-Based Structure Learning. PRASA-RobMech International Conference, November 2017. |
| 2. J. Perlow, B. Rosman, B. Hayes, P. Ranchod. Raw Material Selection for Object Construction. PRASA-RobMech International Conference, November 2017. |
| 3. L. Darlow, B. Rosman. Fingerprint Minutiae Extraction using Deep Learning. International Joint Conference on Biometrics, October 2017. |
| 4. B. van Niekerk, A. Damianou, B. Rosman. Online Constrained Model-based Reinforcement Learning. Uncertainty in Artificial Intelligence, August 2017. |
| 5. A. Earle, A. Saxe, B. Rosman. Hierarchical Subtask Discovery With Non-Negative Matrix Factorization. Workshop on Lifelong Learning: A Reinforcement Learning Approach at ICML, August 2017. |
| 6. A. Saxe, A. Earle, B. Rosman. Hierarchy Through Composition with Multitask LMDPs. International Conference on Machine Learning, August 2017. |
| 7. A. Saxe, A. Earle, B. Rosman. Hierarchy Through Composition with Multitask LMDPs. International Conference on Machine Learning, August 2017. [Supplementary Material] |
| 8. O.C. Görür, B. Rosman, G. Hoffman, S. Albayrak. Toward Integrating Theory of Mind into Adaptive Decision-Making of Social Robots to Understand Human Intention. Workshop on the Role of Intentions in Human-Robot Interaction at the International Conference on Human-Robot Interaction, March 2017. |
| 9. S. James, G.D. Konidaris, B. Rosman. An Analysis of Monte Carlo Tree Search. Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, February 2017. |
2016
| 1. A. Saxe, A. Earle, B. Rosman. Hierarchy through Composition with Linearly Solvable Markov Decision Processes. Technical report, December 2016. |
| 2. R. Berman, R. Benade, B. Rosman, P. Nordengen. Hyperformance: Predicting High-speed Performance of a B-Double. Fourteenth International Symposium on Heavy Vehicle Transport Technology, November 2016. |
| 3. M. Hiratsuka, N. Makondo, B. Rosman, O. Hasegawa. Trajectory Learning from Human Demonstrations via Manifold Mapping. IEEE/RSJ International Conference on Intelligent Robots and Systems, October 2016. |
| 4. S. James, B. Rosman, G. Konidaris. An Investigation into the Effectiveness of Heavy Rollouts in UCT. General Intelligence in Game-Playing Agents (GIGA'16) Workshop at IJCAI, July 2016. |
| 5. B. Rosman, M. Hawasly, S. Ramamoorthy. Bayesian Policy Reuse. Machine Learning Journal, 104(1), pp. 99-127, June 2016. |
| 6. P. Hernandez-Leal, M. Taylor, B. Rosman, E. L. Sucar, E. Munoz de Cote. A Bayesian approach for Learning and Tracking Switching, Non-stationary Opponents. Autonomous Agents and Multiagent Systems, May 2016. [Extended Abstract] |
| 7. W. Masson, P. Ranchod, and G. Konidaris. Reinforcement Learning with Parameterized Actions. Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, February 2016. |
| 8. P. Hernandez-Leal, M. Taylor, B. Rosman, E. L. Sucar, E. Munoz de Cote. Identifying and Tracking Switching, Non-stationary Opponents: a Bayesian Approach. Workshop on Multiagent Interaction without Prior Coordination (MIPC), at AAAI, February 2016. |
2015
| 1. R. Ajoodha, R. Klein, B. Rosman. Single-labelled Music Genre Classification Using Content-Based Features. PRASA-RobMech International Conference, November 2015. |
| 2. R. Berman, R. Benade, B. Rosman. Autonomous Prediction of Performance-based Standards for Heavy Vehicles. PRASA-RobMech International Conference, November 2015. |
| 3. N. Makondo, B. Rosman, O. Hasegawa. Knowledge Transfer for Learning Robot Models via Local Procrustes Analysis. IEEE-RAS International Conference on Humanoid Robots, November 2015. |
| 4. P. Ranchod, B. Rosman, G. Konidaris. Nonparametric Bayesian Reward Segmentation for Skill Discovery Using Inverse Reinforcement Learning. IEEE/RSJ International Conference on Intelligent Robots and Systems, September 2015. |
| 5. B. Rosman, B. Hayes, B. Scassellati. Enhancing Agent Safety through Autonomous Environment Adaptation. Proceedings of the 5th joint IEEE International Conference on Development and Learning and on Epigenetic Robotics. Providence, Rhode Island, August 2015. |
| 6. A. Kleinhans, B. Rosman, M. Michalik, B. Tripp, R. Detry. G3DB: A Database of Successful and Failed Grasps with RGB-D Images, Point Clouds, Mesh Models and Gripper Parameters. Workshop on Robotic Hands, Grasping, and Manipulation, at the IEEE International Conference on Robotics and Automation, May 2015. [Extended Abstract] |
| 7. B. Rosman, S. Ramamoorthy. Action Priors for Learning Domain Invariances. IEEE Transactions on Autonomous Mental Development, January 2015. |
2014
| 1. B. Rosman. Context-based Online Policy Instantiation for Multiple Tasks and Changing Environments. RobMech/PRASA/AfLaT, November 2014. |
| 2. B. van Eden, B. Rosman, D. Withey, T. Ratshidaho, M. Keaikitse, D. Masha, A. Kleinhans, A. Shaik. CHAMP: a Bespoke Integrated System for Mobile Manipulation. RobMech/PRASA/AfLaT, November 2014. |
| 3. B. Rosman. Behavioural Domain Knowledge Transfer for Autonomous Agents. AAAI Fall Symposium on Knowledge, Skill, and Behavior Transfer in Autonomous Robots, November 2014. |
| 4. B. Rosman. Feature Selection for Domain Knowledge Representation through Multitask Learning. IEEE International Conference on Development and Learning and on Epigenetic Robotics (ICDL-EpiRob), October 2014. |
| 5. A. Kleinhans, R. Detry, S. Thill, B. Rosman, B. Tripp. Modelling primate control of grasping for robotics applications. Second Workshop on Affordances: Visual Perception of Affordances and Functional Visual Primitives for Scene Analysis (with ECCV), September 2014. |
| 6. B. Rosman. Learning Domain Abstractions for Long Lived Robots. PhD Thesis. The University of Edinburgh, August 2014. |
| 7. M.M.H. Mahmud, B. Rosman, S. Ramamoorthy, P. Kohli. Adapting Interaction Environments to Diverse Users through Online Action Set Selection. In Proc. AAAI Workshop on Machine Learning for Interactive Systems (AAAI-MLIS), July 2014. |
| 8. B. Rosman, S. Ramamoorthy. Giving Advice to Agents with Hidden Goals. In Proc. International Conference on Robotics and Automation (ICRA), May 2014. |
| 9. B. Rosman, S. Ramamoorthy, M.M.H. Mahmud, P. Kohli. On User Behaviour Adaptation Under Interface Change. In Proc. International Conference on Intelligent User Interfaces (IUI), February 2014. |
| 10. M.M.H. Mahmud, M. Hawasly, B. Rosman, S. Ramamoorthy. Clustering Markov Decision Processes for Continual Transfer. Technical Report, University of Edinburgh, January 2014. |
2013 AND EARLIER
| 1. S. Ramamoorthy, M.M.H. Mahmud, B. Rosman, P. Kohli. Latent-variable MDP models for adapting the interaction environment of diverse users. Technical Report, University of Edinburgh, January 2013. |
| 2. B. Rosman, S. Ramamoorthy. What Good are Actions? Accelerating Learning using Learned Action Priors. IEEE International Conference on Development and Learning (ICDL-EpiRob), November 2012. [Paper of Excellence Award] |
| 3. B. Rosman, S. Ramamoorthy. A Multitask Representation using Reusable Local Policy Templates. AAAI 2012 Spring Symposium Series on Designing Intelligent Robots: Reintegrating AI, March 2012. |
| 4. B. Rosman, S. Ramamoorthy. Learning Spatial Relationships between Objects. International Journal of Robotics Research, Special Issue on Semantic Perception for Robots in Indoor Environments, vol. 30, 11: pp. 1328-13, September 2011. |
| 5. B. Rosman, S. Ramamoorthy. A Game Theoretic Procedure for Learning Hierarchically Structured Strategies. IEEE International Conference on Robotics and Automation, May 2010. |
| 9. S. Rauchas, B. Rosman, G.D. Konidaris and I.D. Sanders. Language Performance at High School and Success in First Year Computer Science. SIGCSE Technical Symposium on Computer Science Education, March 2006. |