[R] Dual Cognitive Architecture: Incorporating Biases and Multi-Memory Systems for Lifelong Learning

**arXiv**: [https://arxiv.org/abs/2310.11341](https://arxiv.org/abs/2310.11341)

**OpenReview**: [https://openreview.net/forum?id=PEyVq0hlO3](https://openreview.net/forum?id=PEyVq0hlO3)

**Code**: [https://github.com/NeurAI-Lab/DUCA](https://github.com/NeurAI-Lab/DUCA)

**Dataset**: [https://github.com/NeurAI-Lab/DN4IL-dataset](https://github.com/NeurAI-Lab/DN4IL-dataset)

**Video**: [https://www.youtube.com/watch?v=08tfpjvUGqs](https://www.youtube.com/watch?v=08tfpjvUGqs)

**Abstract**:

>Artificial neural networks (ANNs) exhibit a narrow scope of expertise on stationary independent data. However, the data in the real world is continuous and dynamic, and ANNs must adapt to novel scenarios while also retaining the learned knowledge to become lifelong learners. The ability of humans to excel at these tasks can be attributed to multiple factors ranging from cognitive computational structures, cognitive biases, and the multi-memory systems in …

abstract adapt anns artificial artificial neural networks become continuous data dynamic excel expertise humans independent knowledge machinelearning multiple narrow networks neural networks novel tasks world