Continuous Learning Process

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A Continuous Learning Process is a learning process that involves ongoing and adaptive learning, allowing systems to evolve and improve in real-time.

  • Context:
    • It can adapt to new data and changing environments without the need for complete retraining.
    • It emphasizes ongoing, adaptive learning in real-time.
    • It happens in real-time, allowing for immediate adaptations.
    • It adapts to new data without necessarily requiring complete retraining.
    • It can be implemented in online learning systems where the model is updated as new data arrives.
    • It can enhance the performance of systems in dynamic and real-time applications, such as autonomous vehicles and financial trading systems.
    • It can be applied in artificial intelligence to enable adaptive systems that respond to user behavior and feedback.
    • It often employs online learning and adaptive algorithms.
    • It focuses on evolving and improving in response to new data and changing environments.
    • It can range from simple real-time updates to sophisticated adaptive algorithms.
    • ...
  • Example(s):
  • Counter-Example(s):
    • A Batch Learning system that requires complete retraining with the entire dataset for updates.
  • See: Real-Time Learning System, Adaptive Algorithm, Online Learning System.


References

2024


  1. Department of Education and Science (2000). Learning for Life: Paper on Adult Education. Dublin: Stationery Office.
  2. Merriam, S. B. & Caffarella, R.S. (2007) Learning in adulthood: A comprehensive guide. San Francisco: Josseey-Bass (3rd. Edition)