Challenge
- Optimizing decision-making in complex, dynamic environments using the example of logistics warehouse control
- Sensitivity analysis / increasing the transparency of an AI using the example of a trained reinforcement learning agent
Solution
- Department store simulator used as a basis for training an AI
- Generic reinforcement learning algorithms learn desired behavior (e.g., maximizing job throughput) through interaction with the simulator
Benefit
- Optimization of goods handling in a warehouse
- Support of employees in dispatching
Your contact
AI from msg – Made in Europe
With artificial intelligence, we want to drive forward the use of AI in organisations faster and more successfully. What sets us apart: Forward-looking consulting services and products to enable value creation through data.