Your team is running a simulation-based optimization exercise to increase routing efficiency.

Unsupervised Learning

Reinforcement Learning

Supervised Learning

All would work equally well

B

Reinforcement Learning is defined in CPMAI as the paradigm where agents learn optimal actions via interactions labeled by reward/punishment signals—essentially a “trial and error” process. Domain III of the CPMAI Exam Content Outline covers “Design reinforcement learning approaches with appropriate agents and environments,” confirming that simulation-based, trial-and-error optimization is the hallmark of Reinforcement Learning .