Reading List

Please use this Google Sheet to add your papers:
https://docs.google.com/spreadsheets/d/1UEktxZXLDDbzabDu66PeBWDxjZRoWO1dAC2zACzaKWU/edit?usp=sharing

If you can, try to find a paper that fits one or more of our main topics: (1) Biological Intelligence, (2) AI Interpretability, (3) Agent Learning, (4) Agent Economics, (5) Agent Limitations and Future Challenges. These can also include older papers, preprints, reviews, etc. Below are some examples:

1. Biological computation and computational biology: survey, challenges, and discussion
   • https://link.springer.com/article/10.1007/s10462-020-09951-1
2. A world survey of artificial brain projects, Part II: Biologically inspired cognitive architectures
   • https://www.sciencedirect.com/science/article/abs/pii/S0925231210003498
3. Brain-inspired Artificial Intelligence: A Comprehensive Review
   • https://arxiv.org/abs/2408.14811
4. Continual Learning with Hebbian Plasticity in Sparse and Predictive Coding Networks: A Survey and Perspective
   • https://arxiv.org/abs/2407.17305
5. On Interpretability of Artificial Neural Networks: A Survey
   • https://ieeexplore.ieee.org/abstract/document/9380482
6. Explainable AI (XAI): A systematic meta-survey of current challenges and future opportunities
   • https://www.sciencedirect.com/science/article/pii/S0950705123000230
7. Neuroscience-Inspired Artificial Intelligence
   • https://www.cell.com/neuron/fulltext/S0896-6273(17)30509-3?imm_mid=0f4e52&cmp=em-data-na-na-newsltr_ai_20170731
8. Biological underpinnings for lifelong learning machines
   • https://www.nature.com/articles/s42256-022-00452-0
9. Brain-Inspired Computing: A Systematic Survey and Future Trends
   • https://ieeexplore.ieee.org/abstract/document/10636118
10. Spiking Neural Networks and Bio-Inspired Supervised Deep Learning: A Survey
    • https://arxiv.org/abs/2307.16235
11. Bottom-Up and Top-Down Approaches for the Design of Neuromorphic Processing Systems: Tradeoffs and Synergies Between Natural and Artificial Intelligence
    • https://ieeexplore.ieee.org/abstract/document/10144567
12. A survey of brain-inspired AI and its engineering
    • https://www.tmrjournals.com/public/articlePDF/20201130/4700bd8edfa25fa77a7f9fe5dd8a5a56.pdf
13. Research Advances and New Paradigms for Biology-inspired Spiking Neural Networks
    • https://arxiv.org/abs/2408.13996
14. Modeling, Replicating, and Predicting Human Behavior: A Survey
    • https://dl.acm.org/doi/full/10.1145/3580492
15. Evolutionary design of neural network architectures: a review of three decades of research
    • https://link.springer.com/article/10.1007/s10462-021-10049-5
16. Brain-inspired learning in artificial neural networks: A review
    • https://pubs.aip.org/aip/aml/article/2/2/021501/3291446
17. A hierarchical taxonomic survey of spiking neural networks
    • https://link.springer.com/article/10.1007/s12293-022-00373-w
18. Reliable interpretability of biology-inspired deep neural networks
    • https://www.nature.com/articles/s41540-023-00310-8
19. The New Generation Brain-Inspired Sparse Learning: A Comprehensive Survey
    • https://ieeexplore.ieee.org/abstract/document/9762529
20. Nature-Inspired Algorithms: A Comprehensive Review
    • https://www.taylorfrancis.com/chapters/edit/10.1201/9780429453427-1/nature-inspired-algorithms-comprehensive-review-essam-houssein-mina-younan-aboul-ella-hassanien
21. A Study of Biology-inspired Algorithms Applied to Long Short-Term Memory Network Training for Time Series Forecasting
    • https://ieeexplore.ieee.org/abstract/document/9632070
22. Perforated Backpropagation: A Biology Inspired Extension to Artificial Neural Networks
    • https://static1.squarespace.com/static/6659cb967ef4d95bd21daaeb/t/675108a9f919fd57d12ff576/1733363882182/Perforated+Backpropagation+-+NeurIPS.pdf
23. Applications and Evaluations of Bio-Inspired Approaches in Cloud Security: A Review
    • https://ieeexplore.ieee.org/abstract/document/9209994
24. Biology inspired growth in meta-learning
    • https://dl.acm.org/doi/abs/10.1145/3520304.3533945
25. Structure and Control of Biology-inspired Networks
    • https://arxiv.org/abs/2410.06990
26. Evolutionary Deep Learning
    • https://books.google.com/books?hl=zh-CN&lr=&id=k1nGEAAAQBAJ&oi=fnd&pg=PR18&dq=survey+biology-inspired+deep+learning&ots=nrddR35zT4&sig=HJtmvFcaGPJkC3CBP8OnE3gS8-o#v=onepage&q&f=false
27. Toward Large-scale Spiking Neural Networks: A Comprehensive Survey and Future Directions
    • https://arxiv.org/abs/2409.02111