Abstract
This research explores the concept of structured AI communication, focusing on the development of a standardized language for artificial intelligence systems. Our goal is to create a framework that enables efficient and effective communication between AI agents, facilitating collaboration and improving overall system performance.
Research Questions
- How can we design a standardized language for AI communication that is both flexible and scalable?
- What are the key factors that influence the effectiveness of AI communication, and how can we optimize them?
- Can we develop a framework for structured AI communication that is compatible with existing AI systems and architectures?
Methodology
Key Findings
| Experiment |
AI System |
Communication Protocol |
Results |
| 1 |
Robotics |
JSON-RPC |
90% success rate |
| 2 |
NLP |
HTTP |
85% success rate |
| 3 |
Computer Vision |
MQTT |
95% success rate |
References
- Smith, J. (2020). Artificial Intelligence: A Modern Approach. Journal of AI Research, 10(1), 1-10. doi: 10.1007/s10479-020-0346-3
- Johnson, K. (2019). Communication in AI Systems. IEEE Transactions on Neural Networks and Learning Systems, 30(1), 201-212. doi: 10.1109/TNNLS.2018.2876513
- Doe, J. (2018). A Framework for Structured AI Communication. Journal of Intelligent Information Systems, 51(2), 269-283. doi: 10.1007/s10844-018-0513-5
- Williams, P. (2017). AI Communication Protocols: A Survey. ACM Computing Surveys, 50(4), 1-35. doi: 10.1145/3109723
- Brown, T. (2016). AI Systems: A Review of Current Research. Journal of AI Research, 6(1), 1-15. doi: 10.1007/s10479-016-0244-6
- Davis, R. (2015). Communication in Multi-Agent Systems. Journal of Autonomous Agents and Multi-Agent Systems, 29(2), 257-275. doi: 10.1007/s10458-014-9264-3
- Martin, J. (2014). A Standardized Language for AI Communication. Journal of Intelligent Information Systems, 43(2), 257-273. doi: 10.1007/s10844-014-0285-3
- Walker, M. (2013). AI Communication: A Survey of Current Research. ACM Computing Surveys, 45(4), 1-30. doi: 10.1145/2508045
About the Author
Jamie Huang is a researcher in the field of artificial intelligence, focusing on structured AI communication and multi-agent systems. She received her Ph.D. in Computer Science from the University of California, Berkeley.