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What is the fringe in the context of search algorithms?
Jul 6, 2019 · In English, the fringe is (also) defined as the outer, marginal, or extreme part of an area, group, or sphere of activity. In the context of AI search algorithms, the state (or search) …
A* and uniform-cost search are apparently incomplete
Nov 24, 2019 · The evaluation function is used to choose the next node to visit from the fringe, which is the set of nodes that can potentially be visited. Whenever we visit a node, we remove …
What are the differences between A* and greedy best-first search?
Aug 30, 2019 · What are the differences between the A* algorithm and the greedy best-first search algorithm? Which one should I use? Which algorithm is the better one, and why?
Why is A* optimal if the heuristic function is admissible?
Apr 13, 2018 · A heuristic is admissible if it never overestimates the true cost to reach the goal node from n n. If a heuristic is consistent, then the heuristic value of n n is never greater than …
What is the difference between tree search and graph search?
There is always a lot of confusion about this concept, because the naming is misleading, given that both tree and graph searches produce a tree (from which you can derive a path) while …
machine learning - What is a fully convolution network? - Artificial ...
Jun 12, 2020 · Fully convolution networks A fully convolution network (FCN) is a neural network that only performs convolution (and subsampling or upsampling) operations. Equivalently, an …
How does the uniform-cost search algorithm work?
Nov 10, 2019 · What is the uniform-cost search (UCS) algorithm? How does it work? I would appreciate seeing a graphical execution of the algorithm. How does the frontier evolve in the …
norvig russell - What does the statement with the max do in the ...
Mar 20, 2020 · (If the g+h cost is larger, then we know the state wasn't previously expanded and it wasn't previously the state on the fringe with the minimum edge cost.) The linked paper gives …
game ai - Artificial Intelligence Stack Exchange
I have extensively researched now for three days straight trying to find which algorithm is better in terms of which algorithm uses up more memory. I know uninformed algorithms, like depth-first …
What are alternatives to PCA for time series data?
Feb 3, 2024 · I have some data (20 stock price time series) and want to compare different approaches for dimensionality reduction other than PCA (I want to fit only 2 variables in my AR …
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