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A domain-agnostic approach for characterization of lifelong learning systems

Megan M. Baker, Alexander New, Mario Aguilar-Simon, Ziad Al-Halah, Sébastien M. R. Arnold, Ese Ben-Iwhiwhu, Andrew Brna, Ethan Brooks, Ryan C. Brown, Zachary Daniels, Anurag Daram, Fabien Delattre, Ryan Dellana, Eric Eaton, Haotian Fu, Kristen Grauman, Jesse Hostetler, Shariq Iqbal, David Kent, Nicholas Ketz, Soheil Kolouri, George Konidaris, Dhireesha Kudithipudi, Erik Learned-Miller, Seungwon Lee, Michael L. Littman, Sandeep Madireddy, Jorge A. Mendez, Eric Q. Nguyen, Christine Piatko, Praveen K. Pilly, Aswin Raghavan, Abrar Rahman, Santhosh Kumar Ramakrishnan, Neale Ratzlaff, Andrea Soltoggio, Peter Stone, Indranil Sur, Zhipeng Tang, Saket Tiwari, Kyle Vedder, Felix Wang, Zifan Xu, Ángel Yanguas-Gil, Harel Yedidsion, Shangqun Yu, Gautam K. Vallabha

2023Neural Networks16 citationsDOIOpen Access PDF

Topics & Concepts

Computer scienceCharacterization (materials science)Lifelong learningDomain (mathematical analysis)Artificial intelligenceMachine learningCognitive scienceNanotechnologyPsychologyMaterials scienceMathematicsPedagogyMathematical analysisIntelligent Tutoring Systems and Adaptive LearningMachine Learning and AlgorithmsOnline Learning and Analytics
A domain-agnostic approach for characterization of lifelong learning systems | Litcius