Peer learning refers to settings where multiple agents improve by exchanging information or imitating each other rather than relying on a central teacher. In multi-agent systems it covers cooperative protocols for sharing experience.
Semantic Classification
Content
- Peer learning describes mechanisms by which agents of comparable capability raise their performance through mutual exchange, such as sharing observations, policies or learned models. Unlike teacher-student distillation, no single agent is assumed to be authoritative.
- In multi-agent reinforcement learning, peer learning can speed up training by letting agents pool experience or coordinate exploration. The idea draws on collaborative learning and connects to knowledge sharing across distributed systems.