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This is achieved by trading optimality, completeness, accuracy, or precision for speed.In a way, it can be considered a shortcut.” The objective of a heuristic algorithm is to apply a rule of thumb approach to produce a solution in a reasonable time frame that is good enough for solving the problem at hand.There is no guarantee that the solution found will be the most accurate or optimal solution for the given problem.
For instance, by looking for words associations, an algorithm can narrow down the meaning of words especially when a word can have two different meanings: e.g.
When using Google search a user types: “Raspeberry Pi Hardware” We can deduct that in this case Raspberry has nothing to do with the piece of fruit, so there is no need to give results on healthy eating, cooking recipes or grocery stores…
Let’s consider the above scenario when investigating all the possible moves for this white pawn.
Can the computer make a quick decision as to what would most likely be the best option?
Instead it will apply a few rules of thumb to quickly discard some moves while focusing on key moves that are more likely to lead to a victory.
When analysing the meaning of a user input, for instance when a user asks a question on a search engine or interacts with a Google Home or Amazon Echo device, an algorithm tries to make sense of the user inputs.Word associations, analysis of context, previous searches history and current trends/search engine statistics can be used in a heuristic algorithm to speed up the search process. This is the case for search engines to return search results very efficiently, profiling algorithms which can be used by a marketing department to identify members of a target audience and their behaviours, data analysis in scientific research (e.g.medicine to identify cause/effect correlations between large data sets).However such an algorithm would have to investigate far too many possible moves and would quickly become too slow and too demanding in terms of memory resources in order to perform effectively.It is hence essential to use a heuristic approach to quickly discard some moves which would most likely lead to a defeat while focusing on moves that would seem to be a good step towards a win!Sometimes your algorithm need to collect or analyse data before applying heuristic to make a decision.This can be done by providing the computer with some data or by implementing an algorithm based on machine learning.You can investigate how machine learning can be used in a game of Top Trumps by reading this blog post.Heuristic methods can be used when developing algorithms which try to understand what the user is saying, or asking for.Heuristic approaches do not always give you the best solution.Can you explain how this could be the case with this scenario?