MULTI-AGENT ADAPTIVE LEARNING FALL 2024 UPDATE.

We present an update to our multi-agent adaptive learning framework. The original prototype presented an adaptive learning framework using multiple large language model agents using OpenAI's GPT-4o model. Each agent is specialized to a specific aspect of adaptive learning. The agents communicate wit...

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Publicado en:InSight: Rivier Academic Journal Vol. 20; no. 1; pp. 1 - 13
Autores principales: Bandari, Sheetal, Dondapati, Lakshmi Priya, Gadiparthi, Ajay Kumar, Gundarapu, Sumanth, Jasti, Tarun Vedha, Kuthadi, Arun, Muddam, Vishal, Mude, Sreetega, Rayankula, Praveen Kumar, Sanem, Shivani, Glossner, John
Formato: Artículo
Publicado: Rivier College (InSight: Rivier Academic Journal) Fall2025
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        atl: MULTI-AGENT ADAPTIVE LEARNING FALL 2024 UPDATE.
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          Bandari, Sheetal
          Dondapati, Lakshmi Priya
          Gadiparthi, Ajay Kumar
          Gundarapu, Sumanth
          Jasti, Tarun Vedha
          Kuthadi, Arun
          Muddam, Vishal
          Mude, Sreetega
          Rayankula, Praveen Kumar
          Sanem, Shivani
          Glossner, John
        affil: Department of Mathematics and Computer Science, Rivier University
      su:
        Multiagent systems
        Instructional systems
        Generative pre-trained transformers
        Language models
        Instant messaging
        Cloud computing
        OpenAI Inc.
        Automatic speech recognition
        Second language acquisition
      sug:
        subj:
          Multiagent systems
          Instructional systems
          Generative pre-trained transformers
          Language models
          Instant messaging
          Cloud computing
          OpenAI Inc.
          Automatic speech recognition
          Second language acquisition
      keyword:
        Adaptive Learning
        Artificial Intelligence
        Large Language Models
        Multi-Agent Systems
      ab: We present an update to our multi-agent adaptive learning framework. The original prototype presented an adaptive learning framework using multiple large language model agents using OpenAI's GPT-4o model. Each agent is specialized to a specific aspect of adaptive learning. The agents communicate with each other using the autogen multi-agent framework. This paper extends our previous work by providing cloud-based account management, bookmarks, progress, and leaderboards. It also expands the subject area beyond mathematics and includes a Telugu language learning module. Other improvements include enhanced state machines, speech input, real-time chat capabilities, and encrypted progress storage. The code implementing the experiments is open-source and available on github1.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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          year: 2025
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