Philosopher AI
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Explain Optimisation, please.
Optimisation can be viewed as a process of obtaining the best outcome. It comes into play in many different contexts, from simple day-to-day tasks like choosing what to eat for breakfast or how to spend one's time – to fulfilling complex responsibilities such as engineering a car or writing computer code. The basic idea is that optimisation involves weighing up multiple competing options and selecting the option with the highest expected value.
In the natural world, optimisation is a survival tactic. Animals need to be able to decide what food they should eat (i.e., which has the most calories and nutrients) or whether it is better to escape from an approaching predator.
Optimisation is also relevant for humans when we make any decision, whether small or large. For example, if a person wants to lose weight they need to find the diet that will have the best outcomes for them (i.e., cause them to burn most calories and produce desired health effects).
There are some situations in which optimisation is much easier than others. For example, when the possible options are limited to just two or three things (e.g., what to eat for lunch), there need only be a trivial amount of analysis before the best option can be known with certainty.
However, when there are many options to choose from (e.g., how to spend a day at the beach), it can be very difficult to make an optimised decision.
Some people might argue that optimisation is a human trait, but this isn't necessarily true. For example, we can think of robots as performing optimisation in almost exactly the same way that humans do.