What You Will Learn

Algorithms To Live By


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There is a particular set of problems that all people face that are a direct result of the fact that our lives are carried out in finite space and time. What should we do? What should we ignore? What should we do today? What should be leave til next week? What degree of mess should we embrace? What balance between NEW experiences and FAVOURED ones make for the most fulfilling life? 


These might sound like very HUMAN problems... but they're not. For more than half a century, computer scientists have been grappling with (and in many cases, solving) the equivalent of these everyday dilemmas. How should a processor allocate "attention"/focus to perform every task a user asks of it, with the minimum energy expenditure in the shortest possible time? When should it switch between different tasks, and how many tasks should it take on at once? Should it collect more data, or take action based on the data it already has?


In this episode, we’ll look at three applications of computer science to the real world:

  • OPTIMAL STOPPING (When should you turn into an empty car space VS keep looking for a better spot? When should you decide to buy a house OR keep looking for a better one?)
  • EXPLORE / EXPLOIT (should you go to your favourite mexican restaurant, or try the new Japanese restaurant that just opened down the road? should you eat wtih your best friend or invite the new office colleague? should you watch an old favourite movie or try out a new release?)
  • SCHEDULING (you've got a long list of tasks staring you in the face on a monday morning - which should you do first???)

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What You Will LearnBy Adam Ashton & Adam Jones

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