While studying I was supposed to get it from a book with long boring descriptions that said many things but gave 0 examples. Then I found this video and it made it so much clearer, thank you. Definetely experience and examples are better than trying to understand some definitions of nodes and problems and what one does with an abstract plane of where the congition is placed. This video is way better.
CS student here. Isn't it still a (priority-based) algorithm in this case (it also has steps) to look for your keys in places it's more likely to find them, and then look in the other places with no priority?
The poster is comparing a terrible algorithm to a sound heuristic. Why not refine the algorithm? Why not start the methodical search along the most likely route and expand outward from there algorithmically?
Certainly the algorithm could be refined and improved, though the heuristic is only sound if the keys are actually in one of those places. If they aren't, it's not particularly useful. The point of the example is to differentiate the two and demonstrate that we tend to think in terms of heuristics (like "most likely" places) when solving problems. Your suggestion is a practical one, but I would say it's an algorithm for which step one is "try using heuristics" :)
It is generally bad pedagogy to refine a concept before your audience has a clearly understood exemplar of that concept. Comparing a terrible algorithm to a sound heuristic is a near-perfect way of making the distinction. His example is unforgettable.
Sure. Imagine you are choosing which movie to buy a ticket for at a cinema. An algorithmic approach would be to read all reviews and ratings for each movie, then calculate a score based on your interests and choose the highest scoring film. This is slow, but would help you to choose a movie you'll enjoy. In contrast, a heuristic might be to choose based on which poster in the lobby appeals to you most. This is faster, but might mean that you choose movies you don't end up enjoying more often.
heuristics and algorithms are not mutually exclusive from a computer science prospective. For example, when doing a majority of code challenges just by looking at the type of code challenge you are given you can tell what type of data structure you can use to solve it. Majority of the time you would use a hash table because of its efficiency.
What is the difference between Heuristic approaches and Reinforcement Learning approaches? Does Reinforcement Learning consist of Heuristic approaches?
well everytime i use heuristics to find my keys i get an anxiety attack and i don't find them so i have to create an algorithm, which takes longer and guess what: i does not work either, just to find out all i need to do is to use the law of attraction and wa-laaa! my keys appear where i looked the first where i started looking!
Pretty straightforward and something I have been looking for. Pls make a video on optimization of a particular problem using heuristics
While studying I was supposed to get it from a book with long boring descriptions that said many things but gave 0 examples. Then I found this video and it made it so much clearer, thank you. Definetely experience and examples are better than trying to understand some definitions of nodes and problems and what one does with an abstract plane of where the congition is placed. This video is way better.
I'm glad it was helpful, I hope my other videos can help for other topics too. Best of luck in your studying!
thank you!! This was a lot more easier to understand. i tend to overcomplicate wordy explainations :')
@@KimMichelle Glad it was helpful!
Heuristic: You look like criminal by the way you walk vs a full Police Back ground check. Profiling.
Like the concept of knowing and believing
You are good at explaining!
Thanks!
CS student here. Isn't it still a (priority-based) algorithm in this case (it also has steps) to look for your keys in places it's more likely to find them, and then look in the other places with no priority?
Thank you, your explanation is very helpful 💐
Glad to hear that!
The poster is comparing a terrible algorithm to a sound heuristic. Why not refine the algorithm? Why not start the methodical search along the most likely route and expand outward from there algorithmically?
Certainly the algorithm could be refined and improved, though the heuristic is only sound if the keys are actually in one of those places. If they aren't, it's not particularly useful. The point of the example is to differentiate the two and demonstrate that we tend to think in terms of heuristics (like "most likely" places) when solving problems. Your suggestion is a practical one, but I would say it's an algorithm for which step one is "try using heuristics" :)
It is generally bad pedagogy to refine a concept before your audience has a clearly understood exemplar of that concept. Comparing a terrible algorithm to a sound heuristic is a near-perfect way of making the distinction. His example is unforgettable.
Great video very clear
Can u give another example of heuristic and algorithm?
Sure. Imagine you are choosing which movie to buy a ticket for at a cinema. An algorithmic approach would be to read all reviews and ratings for each movie, then calculate a score based on your interests and choose the highest scoring film. This is slow, but would help you to choose a movie you'll enjoy. In contrast, a heuristic might be to choose based on which poster in the lobby appeals to you most. This is faster, but might mean that you choose movies you don't end up enjoying more often.
heuristics and algorithms are not mutually exclusive from a computer science prospective. For example, when doing a majority of code challenges just by looking at the type of code challenge you are given you can tell what type of data structure you can use to solve it. Majority of the time you would use a hash table because of its efficiency.
What is the difference between Heuristic approaches and Reinforcement Learning approaches? Does Reinforcement Learning consist of Heuristic approaches?
Sorry, I'm not particularly knowledgeable about machine learning so I don't think I can adequately address this question.
your explained it with cool analogy thx
You're welcome!
thank you. great explaination !
You're welcome!
thank you so so much for making it clear for poor psych students haha love it
You're welcome, glad I can help!
Omg u r amazing, thank you so much ❤
@@pegishay1954 You're welcome!
thank you
Love u bruhhhh❤
Thank you for this!
You're welcome!
well everytime i use heuristics to find my keys i get an anxiety attack and i don't find them so i have to create an algorithm, which takes longer and guess what: i does not work either, just to find out all i need to do is to use the law of attraction and wa-laaa! my keys appear where i looked the first where i started looking!
great explanation
Thanks!
Thank youu❤
You're welcome!
Thanks mollions😻
you are genius
Great video!
Thanks!
Thank you for explaining it clearly. I'm not so smart 🤣
You're welcome, hopefully my videos can help you keep getting smarter!
Gwapooo haha