Cobweb
Cobweb is a clustering model which supports incremental concept learning from fewer examples. The model learns both structure and parameters where the structural expansion is dynamic. It uses multimodal approach which is human like. Future scope is to optimize exisitng model, integrate concept learning with skill learning and organize skills with cobweb.
Related Publications
Nicki Barari, Xin Lian, Christopher J. MacLellan (2026). Robust Incremental Learning of Visual Concepts without Catastrophic Forgetting. Cognitive Systems Research.
Zekun Wang, Ethan Haarer, Tianyi Zhu, Zhiyi Dai, Christopher J. MacLellan (2025). Deep Taxonomic Networks for Unsupervised Hierarchical Prototype Discovery. Proceedings of Advances in Neural Information Processing Systems.
Zekun Wang, Ethan Haarer, Nicki Barari, Christopher J. MacLellan (2025). Taxonomic Networks: A Representation for Neuro-Symbolic Pairing. Proceedings of the 2nd International Conference on Neuro-symbolic Systems.
Anant Gupta, Karthik Singaravadivelan, Zekun Wang (2025). Hierarchical Semantic Retrieval with Cobweb. Proceedings of the Twelfth Annual Conference on Advances in Cognitive Systems.
Nicki Barari, Edward Kim, Christopher J. MacLellan (2025). Explaining Robustness to Catastrophic Forgetting Through Incremental Concept Formation. Proceedings of the Twelfth Annual Conference on Advances in Cognitive Systems.
Xin Lian, Zekun Wang, Christopher J. MacLellan (2025). Efficient and Scalable Masked Word Prediction Using Concept Formation. Cognitive Systems Research.
Xin Lian, Sashank Varma, Christopher J. MacLellan (2024). Cobweb: An Incremental and Hierarchical Model of Human-Like Category Learning. Proceedings of the 46th Annual Conference of the Cognitive Science Society.
Nicki Barari, Xin Lian, Christopher J. MacLellan (2024). Avoiding Catastrophic Forgetting in Visual Classification Using Human Concept Formation. Proceedings of the Eleventh Annual Conference on Advances in Cognitive Systems.
Christopher J. MacLellan, Peter Matsakis, Pat Langley (2022). Efficient Induction of Language Models via Probabilistic Concept Formation. Proceedings of the Tenth Annual Conference on Advances in Cognitive Systems.
Christopher J. MacLellan, Harshil Thakur (2021). Convolutional Cobweb: A Model of Incremental Learning from 2D Images. Proceedings of the Ninth Annual Conference on Advances in Cognitive Systems.
Erik Harpstead, Christopher J. MacLellan (2019). Visualizing the Solution Space of Educational Games using Trestle. Companion Proceedings of the 9th International Conference on Learning Analytics & Knowledge.
Christopher J. MacLellan, Erik Harpstead, Vincent Aleven, Kenneth R. Koedinger (2016). TRESTLE: A Model of Concept Formation in Structured Domains. Advances in Cognitive Systems.
Erik Harpstead, Christopher J. MacLellan, Vincent Aleven (2015). Discovering Knowledge Models in an Open-Ended Educational Game using Concept Formation. Workshop Proceedings of AIED 2015.
Christopher J. MacLellan, Erik Harpstead, Vincent Aleven, Kenneth R. Koedinger (2015). TRESTLE: Incremental Learning in Structured Domains using Partial Matching and Categorization. Proceedings of the Third Annual Conference on Advances in Cognitive Systems.