Some other computer science concepts that can be applied to decision making include algorithms, data structures, machine learning, artificial intelligence, and optimization techniques. Algorithms can help in creating efficient processes for decision making. Data structures can help in organizing and storing data for easy access and manipulation. Machine learning and artificial intelligence can help in making predictions and decisions based on patterns in data. Optimization techniques can help in finding the best solution among a set of possible solutions.

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Algorithms to Live By: The Computer Science of Human Decisions by Brian Christian and Tom Griffiths

Can computer science teach us the secrets of life? Perhaps not, but they can shed light on how certain everyday processes work and how to exploit them...

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Life is full of situations that require us to make the best possible decision in the shortest amount of time. Drivers search for the perfect parking space. Managers search for the best job candidate for a job, and property owners must decide on whether or not to accept a sale offer before the real estate market changes again. This dilemma is called "optimal stopping."

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The concept of optimal stopping can apply to academic research in several ways. For instance, researchers often need to decide when to stop collecting data or when to stop a study. This decision can be based on a variety of factors, such as the quality of the data collected, the time and resources available, and the objectives of the research. Optimal stopping can help researchers make these decisions in a more systematic and efficient way.

Some other decision-making dilemmas that can be explained using algorithms include choosing the best time to buy or sell stocks, determining the optimal route for a delivery truck, deciding when to replace aging equipment, and selecting the best strategy in a game of chess. Algorithms can also be used to solve problems in machine learning and artificial intelligence, such as classifying images or predicting future events.

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