The proposed approach to managing short-term memory in chatbots enhances conversation flow by preserving vital context, optimizing storage, and utilizing summarization techniques.
This memory structure allows for dynamic, efficient handling of conversational context while maintaining responsiveness, ensuring that users experience seamless interactions with the chatbot.
Through mathematical formalization, the chatbot's memory is represented as a list of exchanges, preserving essential dialogue while managing space and enhancing understanding.
Asynchronous memory management ensures that chatbot responsiveness is not compromised, allowing ongoing conversations to feel coherent and immediate, regardless of length.
#chatbot-development #memory-management #conversational-ai #asynchronous-techniques #dynamic-memory-structure
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