Navigating the AI Frontier 2024
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Endnotes
1 Vaswani, A., et al. (2023). Attention is all you need. https://arxiv.org/abs/1706.03762
2 World Economic Forum. (2024). AI value alignment: Guiding artificial intelligence towards shared human goals.
https://www.weforum.org/publications/ai-value-alignment-guiding-artificial-intelligence-towards-shared-human-goals/
3 Russell, S., & Norvig, P . (2021) Artificial intelligence: A modern approach (4th ed.). Prentice Hall.
4 Anglen, J. (n.d.). What are AI agents? Artificial Intelligence agents capabilities. Rapid Innovation. Retrieved November 1,
2024, from https://www.rapidinnovation.io/post/what-are-ai-agents-agents-in-artificial-intelligence-explained
5 International Organization for Standardization/International Electrotechnical Commission. (2022). ISO/IEC 22989:2023:
Information technology – artificial intelligence – artificial intelligence concepts and terminology. https://www.iso.org/
standard/74296.html
6 Russell, S., & Norvig, P . (2021). Artificial intelligence: A modern approach (4th ed.). Prentice Hall.
7 Vaswani, A., et al. (2023). Attention is all you need. https://arxiv.org/abs/1706.03762
8 Sodhani, S., et al. (2022). An introduction to lifelong supervised learning. https://arxiv.org/abs/2207.04354
9 Buffet, O., Pietquin, O., & Weng, P . (2020). Reinforcement learning. https://arxiv.org/pdf/2005.14419
10 Kaufmann, T., Wenig, P ., Bengs, V., & Hüllermeier, E. (2024). A survey of reinforcement learning from human feedback.
https://arxiv.org/abs/2312.14925
11 Neyshabur, B., Sedghi, H., & Zhang, C. (2021). What is being transferred in transfer learning? https://arxiv.org/
abs/2008.11687
12 Farahani, A., Pourshojae, B., Rasheed, K., & Arabnia, H. (2021). A concise review of transfer learning. https://arxiv.org/
abs/2104.02144
13 Russell, S., & Norvig, P . (2021) Artificial intelligence: A modern approach (4th ed.). Prentice Hall.
14 Ibid.
15 Ibid.
16 Ibid.
17 World Economic Forum. (2023). Data equity: Foundational concepts for generative AI. https://www.weforum.org/
publications/data-equity-foundational-concepts-for-generative-ai/
18 Zhao, P ., Jin, Z., & Cheng, N. (2023). An in-depth survey of large language model-based artificial intelligence agents.
https://arxiv.org/abs/2309.14365
19 Wei, J., et al. (2023). Chain-of-thought prompting elicits reasoning in large language models. https://arxiv.org/
abs/2201.11903
20 Simankov, V., Onishchenko, S., Buchatskiy, P ., & Teploukhov, S. (2023). An approach to the definition of system
intelligence in the management of complex systems. IEEE Xplore. https://ieeexplore.ieee.org/document/10159122
21 Wang, J., et al. (2024). Mixture-of-agents enhances large language model capabilities. https://arxiv.org/abs/2406.04692
22 Pendleton, S. D. et al. (2017). Perception, planning, control, and coordination for autonomous vehicles. Machines, 5(1).
MDPI. https://www.mdpi.com/2075-1702/5/1/6#:~:text=Perception%20refers%20to%20the%20ability,by%20the%20
higher%20level%20processes
23 Mahela, O., et al. (2022). Comprehensive overview of multi-agent systems for controlling smart grids. CSEE Journal of
power and energy systems, 8(1). SciOpen.
24 Ibid.
25 Ibid.
26 LangGraph. (n.d.). Conceptual guide for multi-agent systems. Retrieved November 1, 2024, from
https://langchain-ai.github.io/langgraph/concepts/multi_agent/
27 US Department of Transportation (2019). Vehicle-to-everything (V2X) communications.
https://www.transportation.gov/v2x
28 Han, S., et al. (2024). LLM multi-agent systems: Challenges and open problems. https://arxiv.org/abs/2402.03578
29 Saha, H., Venkataraman, V., Speranzon, A., & Sarkar, S. (2019). A perspective on multi-agent communication for
information fusion. https://arxiv.org/abs/1911.03743v1
30 Zhu, C., Dastani, M., & Wang, S. (2024). A survey of multi-agent reinforcement learning with communication.
https://arxiv.org/abs/2203.08975
31 Baroni, M., Dessi, R., & Lazaridou, A. (2022). Emergent language-based coordination in deep multi-agent systems. ACL
Anthology. https://aclanthology.org/2022.emnlp-tutorials.3/
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