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HumAine-Chatbot: Real-Time Personalized Conversational AI via Reinforcement Learning

작성자
  • Haebom

Author

Georgios Makridis, Georgios Fragiadakis, Jorge Oliveira, Tomaz Saraiva, Philip Mavrepis, Georgios Fatouros, Dimosthenis Kyriazis

Outline

HumAIne-chatbot is an AI-based conversational agent that provides personalized conversations based on user characteristics. It pre-trains various GPT-generated virtual personas to establish extensive prior knowledge about user types. During real-time interactions, it uses a reinforcement learning agent to combine implicit signals (typing speed, emotions, engagement time, etc.) with explicit feedback (likes/dislikes) to refine the user model. The refined user profiles are dynamically reflected in the conversation policy, adjusting both content and style in real time. Experiments with 50 synthetic personas showed that when personalized features were enabled, user satisfaction, personalized accuracy, and task completion rates improved. Statistical analysis confirmed significant differences between the personalized condition and the control group.

Takeaways, Limitations

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Takeaways:
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Demonstrating the effectiveness of a personalized conversation system through AI-based user profiling.
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Demonstrating the effectiveness of a user model improvement strategy that combines implicit and explicit signals.
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Identifying the potential for improving user experience through real-time conversational content and style adjustments.
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Statistically significant results were obtained for improved user satisfaction, personalization accuracy, and task completion rates.
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Limitations:
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Only synthetic personas were used in the experiment, and validation using real user data was required.
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Further validation of generalizability across different user types and conversation domains is needed.
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Lack of analysis of the stability and potential performance degradation of long-term use systems.
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Lack of consideration for privacy and ethical issues.
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