I have a question regarding picking the final agent from the archive.
Currently, I set epsilon = 0.5 to have a balanced pick, so the final agent can be supported by enough evaluations and also shows promise.
But I ended up always picking the agents in the early stage of the archive. i.e., a direct child of the initial agent.
I used gpt-5.4-mini as the downstream LLM, and I set the evaluation budget to 200.
Has anyone else met the same problem, could the authors shares more insights on picking the final agent? Thanks in advance.
I have a question regarding picking the final agent from the archive.
Currently, I set epsilon = 0.5 to have a balanced pick, so the final agent can be supported by enough evaluations and also shows promise.
But I ended up always picking the agents in the early stage of the archive. i.e., a direct child of the initial agent.
I used gpt-5.4-mini as the downstream LLM, and I set the evaluation budget to 200.
Has anyone else met the same problem, could the authors shares more insights on picking the final agent? Thanks in advance.