Use of zettelkasten for agent memory
zettelkasten-strat-index may be useful for agent-idea-retrieval and agent-idea-relation-representation for agi-memory
The benefits of using zettelkasten for agent memory are that:
- it is human interprable
- facilitates discovery of relevant ideas
- allows for natural language description of ideas
- links between ideas can have meaning (semantic linking)
- doesn’t enforce rigid structure
Problems which need to be solved:
- how for agent to determine when to store an idea
- how to refactor ideas, prune and make connections to allow better navigation
- delete ideas and combine ideas
- find relevant ideas to link to
- determine when to stop searching through memory
If a zettelkasten is employed:
- for each idea/memory, an agent should store semantic links to other ideas
- these can be added or removed over time as new connections/relevant ideas are discovered
- allows for more efficiently finding relevant ideas when solving problem/carrying out a task
- these can be added or removed over time as new connections/relevant ideas are discovered
- more thoughts on this topic can be found in learning-as-adding-new-functions-to-a-concept-network and ai-agent-memory-optimisation-design
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