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Azure Bonsai Reinforcement Learning Process

Steps to show how to use Bonsai to train a model and deploy

Use Case



Process Flow

Training and deploy

package "exportedname"
requestBody = {
"state": {
"acceptingness": 2,
"num_vehicles": 1.5,
"production_rates": 0.75,
"vehicle_utilizations": 0.1,
"inventory_levels": 1,
"queue_sizes": 2,
"rolling_turnaround_hours": 40,
"accepting_rolling_turnaround_hours": 20,
"rolling_cost_per_products": 40,
"accepting_rolling_cost_per_products": 20,
"time_hours": 4
# Whether each MC should accept orders
# Orders that would normally go to an MC are redirect to the nearest open MC
acceptingness: number<0, 1, >[3],
# Number of vehicles to allocate to each MC
num_vehicles: number<1 .. 3 step 1>[3],
# Hourly production rate at each MC
production_rates: number<50 .. 80>[3]



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