Retroactive learning

Uses your system voice; voice and rate in settings.

Snapshot

≈ 2 min read

Names in other languages

No names in other languages are held for this entry yet.

Article bodies are English and are not machine-translated. A name in another language is not a translation of the article.

Within theories of education, retroactive learning is a delay in understanding an experience, or review of learning experiences when resources become available. Often, it is not possible to learn while an event is occurring because the agent lacks the specific information or resources that it needs to learn. For example, an agent in a realtime environment may not have time to apply an iterative learning algorithm while it is performing a task. However, when a resource like time becomes available, the agent can replay the events and learn from them. Episodic memory allows previous experiences to be relived or rehearsed once resources are available so it can be reanalyzed with new knowledge or additional experiences.

Within theories of education, retroactive learning is a delay in understanding an experience, or review of learning experiences when resources become available. Often, it is not possible to learn while an event is occurring because the agent lacks the specific information or resources that it needs to learn. For example, an agent in a realtime environment may not have time to apply an iterative learning algorithm while it is performing a task. However, when a resource like time becomes available, the agent can replay the events and learn from them. Episodic memory allows previous experiences to be relived or rehearsed once resources are available so it can be reanalyzed with new knowledge or additional experiences.

Text derived from https://en.wikipedia.org/w/index.php?oldid=1137743979 under CC BY-SA 4.0; modifications have been made.

Sources cited in this revision

Extracted from the cited revision's reference blocks; absent citations are not invented.