Artificial Intelligence By Example

Designing datasets in natural language meetings

The reinforcement learning program described in the first chapter can solve a variety of problems involving unlabeled classification in an unsupervised decision-making process. The Q function can be applied indifferently to drone, truck, or car deliveries. It can also be applied to decision-making in games or real life.

However, in a real-life case study problem (such as defining the reward matrix in a warehouse for the AGV, for example), the difficulty will be to design a matrix that everybody agrees with.

This means many meetings with the IT department to obtain data, the SME and reinforcement learning experts. An AGV requires information coming from different sources: daily forecasts and ...