Your team is running a simulation-based optimization exercise to increase routing efficiency. Learning for this exercise is done through “trial and error.” Which type of machine learning approach is being leveraged for this exercise?
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 .
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