Iterative Interaction

Iterative interaction, a process involving repeated exchanges between agents or systems, is a burgeoning research area focusing on improving the efficiency and performance of various applications. Current research emphasizes the development of algorithms and models, such as those based on large language models (LLMs) and game-theoretic frameworks, to optimize these interactions, particularly in human-computer interaction, autonomous driving, and multi-agent systems. This work aims to address challenges like bias amplification, latency, and the need for more robust and adaptable systems, ultimately leading to more effective and human-centered technologies. The impact spans diverse fields, from improving the design of user interfaces and autonomous vehicles to mitigating risks associated with the increasing use of LLMs.