Pitfalls in AI-based Learning - A Supply Chain Example

Recently we were investigating Reinforcement Learning (RL) for a sequential decision-making problem. The RL agent/bot’s function here is to decide on what action to take at any instance when customer requests come in. Interestingly, in hindsight, we observed that maximizing the weighted average of customer satisfaction is the bestaction to take in all instances.

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