Unverified50% confidenceOpinionExact time
The author deliberately avoids full multi-agent reinforcement learning in the production path, because emergent coordination policies are extremely difficult to audit.
1
Sources
50%
Confidence
Long-term
Relevance
10/18/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedOne of the most common failures the author encountered is that agents lack accurate self-awareness of their own capabilities and continuously seek external approval and validation.70% similarUnverifiedThe shared limitation of Hebbian learning and competitive learning is the lack of an explicit optimization objective, making end-to-end fine-tuning for downstream tasks difficult, and they are typically used for feature extraction and representation learning.70% similarUnverified提示工程类工作难以提供严格的理论分析，其有效性更多依赖实验观察69% similarUnverifiedThe cost of adaptive expert suppression is that it may mistakenly mask useful experts, so the suppression strategy needs to be sufficiently lightweight and learnable.69% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1061324API
curl https://kongchang.com/api/v1/knowledge/claims/1061324MCP
get_claim(id=1061324)