Description 1. Agent Should Expand Its Knowledge
Concepts &
Data Source Retrieve/Retrieval Analyze Learn Knowledge Context Opinions Environment Information Inform/Communicate
1. Data Source:
It should have a name.
It should have a description of what the data is, why it is provided, and what it offers.
Should have a type (e.g., 'api', 'text', etc.).
It should be accessible to the agent at all times.
2. There should be a need/gap for the agent to drive its learning.
This should be controlled by the agent itself.
3. The agent should be able to divide its learning into learning tasks (like we humans do) and perform steps to complete these tasks.
4. The learning tasks should be:
Goal-oriented and time-based, meaning the agent should execute these tasks based on the time it sets for itself.
5. The task itself should have a clear end goal and should be:
Atomic (independent of the context).It should have a time of execution and priority.
6. The incoming data should be processed such that it is useful for the agent to add to its knowledge context.
7. Not all data is useful, so only relevant data should be added to its knowledge.
8. The agent's personality will affect its learning progress.
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