Decision-Making is all about selection of optimal decisions, with the right risk and reward balance, in face of uncertainty. It’s one crucial step of the Machine Learning Process and it’s present in all sorts of areas. Based on previous knowledge of data and predictive models, decisions play a vital part in the business problems solutions. Therefore, to achieve efficient solutions, it’s important to analyze the state dynamics, information rate and tradeoffs that take place in each case.
There are some aspects that make Decision-Making scenarios differ from one another. These aspects are the dynamics of state and the dynamics of information. The state dynamics is about how actions impact the current state of the business. On the other hand, the information dynamics is the rate at which it’s possible to gather information, in other words, gather data and analyze it. The combinations of these parameters lead to different Decision-Making scenarios.
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