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Conversational Agents: Goals, Technologies, Vision and Challenges.

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Conversational agents (CAs) are increasingly used across many sectors. This review details their enabling technologies, applications, and future research directions, including ethical considerations for advanced CA development.

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Area of Science:

  • Artificial Intelligence
  • Human-Computer Interaction
  • Natural Language Processing

Background:

  • Conversational agents (CAs) are now prevalent in daily life.
  • CA technology has matured, enabling diverse applications.
  • CAs integrate natural language processing, deep learning, and emotional intelligence.

Purpose of the Study:

  • To review the success of CAs in various domains.
  • To describe the core technologies behind CA development.
  • To categorize CAs by abilities and applications.

Main Methods:

  • Literature review of CA technologies and applications.
  • Analysis of CA evaluation methods and datasets.
  • Identification of future research areas.

Main Results:

  • CAs are successful in commercial, healthcare, educational, and other sectors.
  • Key technologies include NLP, deep learning, and emotional integration.
  • Publicly available datasets and evaluation tools are identified.

Conclusions:

  • CAs offer significant potential across multiple domains.
  • Future research should address ethical and security concerns.
  • This review provides a foundational overview for CA development and deployment.