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Integrating Sensing and Cueing for More Effective Activity Reminders.

, , , , and . AAAI Fall Symposium: AI in Eldercare: New Solutions to Old Problems, volume FS-08-02 of AAAI Technical Report, page 60-66. AAAI, (2008)

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Loss of Plasticity in Continual Deep Reinforcement Learning., , , , and . CoLLAs, volume 232 of Proceedings of Machine Learning Research, page 620-636. PMLR, (2023)Discovering sensor space: Constructing spatial embeddings that explain sensor correlations.. ICDL, page 120-125. IEEE, (2010)Natural Value Approximators: Learning when to Trust Past Estimates., , , , , and . NIPS, page 2120-2128. (2017)The Barbados 2018 List of Open Issues in Continual Learning., , , , , , , , , and . CoRR, (2018)Two Perspectives on Learning Rich Representations from Robot Experience.. AAAI Workshop: Learning Rich Representations from Low-Level Sensors, volume WS-13-12 of AAAI Technical Report, AAAI, (2013)Vector-based navigation using grid-like representations in artificial agents., , , , , , , , , and 16 other author(s). Nat., 557 (7705): 429-433 (2018)Bootstrap learning for object discovery., and . IROS, page 742-747. IEEE, (2004)Scaling-up Knowledge for a Cognizant Robot., and . AAAI Spring Symposium: Designing Intelligent Robots, volume SS-12-02 of AAAI Technical Report, AAAI, (2012)Where Do Actions Come From? Autonomous Robot Learning of Objects and Actions., and . AAAI Spring Symposium: Control Mechanisms for Spatial Knowledge Processing in Cognitive / Intelligent Systems, page 41-46. AAAI, (2007)Factoring the Mapping Problem: Mobile Robot Map-building in the Hybrid Spatial Semantic Hierarchy., , and . Int. J. Robotics Res., 29 (4): 428-459 (2010)