#OFN How Reward Maximization Works in #OpenfabricA I

Learning from Feedback: Agents continuously refine their behavior based on reward signals.

Exploration vs. Exploitation: Balancing between trying new actions (exploration) and choosing known successful ones (exploitation) to find the best long-term policy.

Multi-Agent Collaboration: Multiple agents can work together, sharing insights and strategies to maximize collective rewards across a decentralized network.