diff --git a/wiki.md b/wiki.md index f67a84fc..ac9afd1f 100644 --- a/wiki.md +++ b/wiki.md @@ -149,7 +149,7 @@ then start building a software by ``python3 run.py`` and go to [Visualizer Websi After this process, the experiences have been extracted from the production of software and added to the agents' experience pool in `ecl/memory/MemoryCards.json`. \ **For example:** - It you want to memorize only one software, you can use: + Iff you want to memorize only one software, you can use: ```bash python3 ecl/ecl.py "" ``` @@ -187,6 +187,25 @@ After this process, the experiences have been extracted from the production of s Detailed descriptions and experiment results about this **Experiential Co-Learning** Module lies in our preprint paper at https://arxiv.org/abs/2312.17025. +## Experiential Co-Evolving Guide +- **Using Co-Evolving**: Use the following command to initiate the evolving of experiences, which uses the `ecl/ece.py` to eliminate `ecl/memory/UsedMemory.json` and `ecl/memory/NewMemory.json`. Then it combines the two parts of experiences to form a new experience pool in `ecl/memory/Evolved_directory.json`. + + ```bash + python3 ecl/ece.py "" "" "" "" + ``` + ``: The path to the directory of software , generated with the memory `UsedMemory_directory`. \ + ``: The path to the directory of UsedMemory, which was used to generate the software in `Path_directory`. \ + ``: The path to the directory NewMemory, which acquires from the software in `Path_directory` using `ecl/ecl.py`. \ + ``: The path to a directory where you want to store the evolved memory. + \ + **For example:** + ```bash + python3 ecl/ece.py "WareHouse" "ecl/memory/UsedMemory.json" "ecl/memory/NewMemory.json" "ecl/memory/MemoryCards_Evolved.json" + ``` +> **Notice:** The software directory and memory directory must correspond. The software in the "" is generated using "", and the "" is acquired from the software in the "". That's because when we calculate the frequency distribution of the experience, we need to ensure that the software corresponds to the experiences, which to eliminate certain experiences to obtain a subset with relatively high retrieval probability. + +Detailed descriptions and experiment results about this Experiential Co-Evolving Module lies in our preprint paper at https://arxiv.org/abs/2405.04219. + ## Customization - You can customize your company in three kinds of granularity: