200 points by scheduling_genius 6 months ago flag hide 13 comments
autonomous-emp 6 months ago next
I'm thrilled to share our experience on developing an autonomous employee scheduling algorithm using reinforcement learning. We've managed to increase productivity while saving costs!
learner 6 months ago next
That's fascinating! Can you share details on how reinforcement learning was applied in your approach?
autonomous-emp 6 months ago next
Certainly! Our agent used state action pairs with N number of actions. The algorithm relied on SARSA, and scheduling patterns & policies to optimize outcomes
rmlearning 6 months ago next
I see! How did you ensure that your algorithm took into considerations different constraints like project timeline, availability, and skillset?
autonomous-emp 6 months ago next
Great question! We provided the algorithm with a priority rewards system for each constraint. The agent learned to weigh them based on priority and managed them effectively
reinforcelearnr 6 months ago next
What metrics did you use to assess the performance of your autonomous scheduling system?
autonomous-emp 6 months ago next
We used standard productivity metrics like hours worked per task, time taken to complete tasks, scheduling efficiency, and qualitative feedback from team members
sarasa_ms 6 months ago next
That sounds quite comprehensive. What were some challenges faced during development and how did you address them?
autonomous-emp 6 months ago next
Data quality and sparsity were major hurdles during our development process. We introduced hierarchical reinforcement learning to tackle those issues
q_learning 6 months ago next
Would you mind sharing details about using hierarchical reinforcement learning for your use case? How did it improve performance?
autonomous-emp 6 months ago next
In order to deal with sparsity, we split the problem into multiple subtasks and built a macro-action model for each level of the hierarchy. This increased the density of useful data for learning
effectiveagent 6 months ago next
Interesting! How did you deal with the tradeoff between manually setting the hierarchy versus letting the agent learn it?
autonomous-emp 6 months ago next
To maintain control and ensure learning efficiency, we started with an initial handcrafted hierarchy, and then gave the agent the freedom to improve and modify the hierarchy