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Biological Underpinnings of Lifelong Learning Machines (2022)
D. Kudithipudi, M. Aguilar-Simon, J. Babb, M. Bazhenov, D. Blackiston, J. Bongard, A. P. Brna, S. C. Raja, N. Cheney, J. Clune, A. Daram, S. Fusi, P. Helfer, L. Kay, N. Ketz, Z. Kira, S. Kolouri, J. L. Krichmar, S. Kriegman, M. Levin, S. Madireddy, S. Manicka, A. Marjaninejad, B. McNaughton, R. Miikkulainen, Z. Navratilova, T. Pandit, A. Parker, P. K. Pilly, S. Risi, T. J. Sejnowski, A. Soltoggio, N. Soures, A. S. Tolias, D. Urbina-Melendez, F. J. Valero-Cuevas, G. M. van de Ven, J. T. Vogelstein, F. Wang, R. Weiss, A. Yanguas-Gil, Z. Zou, H. Siegelman
Biological organisms learn from interactions with their environment throughout their lifetime. For artificial systems to successfully act and adapt in the real world, it is desirable to similarly be able to learn on a continual basis. This challenge is known as lifelong learning, and remains to a large extent unsolved. In this Perspective article, we identify a set of key capabilities that artificial systems will need to achieve lifelong learning. We describe a number of biological mechanisms, both neuronal and non-neuronal, that help explain how organisms solve these challenges, and present examples of biologically inspired models and biologically plausible mechanisms that have been applied to artificial systems in the quest towards development of lifelong learning machines. We discuss opportunities to further our understanding and advance the state of the art in lifelong learning, aiming to bridge the gap between natural and artificial intelligence.
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Citation:
Nature Machine Intelligence
, 4, 2022.
Bibtex:
@article{kudithipudi:machint22, title={Biological Underpinnings of Lifelong Learning Machines}, author={D. Kudithipudi and M. Aguilar-Simon and J. Babb and M. Bazhenov and D. Blackiston and J. Bongard and A. P. Brna and S. C. Raja and N. Cheney and J. Clune and A. Daram and S. Fusi and P. Helfer and L. Kay and N. Ketz and Z. Kira and S. Kolouri and J. L. Krichmar and S. Kriegman and M. Levin and S. Madireddy and S. Manicka and A. Marjaninejad and B. McNaughton and R. Miikkulainen and Z. Navratilova and T. Pandit and A. Parker and P. K. Pilly and S. Risi and T. J. Sejnowski and A. Soltoggio and N. Soures and A. S. Tolias and D. Urbina-Melendez and F. J. Valero-Cuevas and G. M. van de Ven, J. T. Vogelstein and F. Wang and R. Weiss and A. Yanguas-Gil and Z. Zou and H. Siegelman}, volume={4}, journal={Nature Machine Intelligence}, month={ }, url="http://nn.cs.utexas.edu/?kudithipudi:machint22", year={2022} }
Areas of Interest
Computational Neuroscience