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What is the fringe in the context of search algorithms? 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) space is usually represented as a graph, where nodes are states and the edges are the connections (or actions) between the corresponding states
How is iterative deepening A* better than A*? The iterative deepening A* search is an algorithm that can find the shortest path between a designated start node and any member of a set of goals The A* algorithm evaluates nodes by combining the
What is the difference between local search and global search . . . The difference between a local search algorithm (like beam search) and a complete search algorithm (like A*) is, for the most part, small Local search algorithms will not always find the correct or optimal solution, if one exists For example, with beam search (excluding an infinite beam width), it sacrifices completeness for greater efficiency by ordering partial solutions by some heuristic
machine learning - What is a fully convolution network? - Artificial . . . Fully convolution networks A fully convolution network (FCN) is a neural network that only performs convolution (and subsampling or upsampling) operations Equivalently, an FCN is a CNN without fully connected layers Convolution neural networks The typical convolution neural network (CNN) is not fully convolutional because it often contains fully connected layers too (which do not perform the
Why is A* optimal if the heuristic function is admissible? The tree search does not remember which states it has already visited, only the "fringe" of states it hasn't visited yet A graph search is a general search strategy for searching graph-structured problems, where it's possible to double back to an earlier state, like in chess (e g both players can just move their kings back and forth)
How does the uniform-cost search algorithm work? 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 case of UCS?
What is the space complexity of breadth-first search? When using the breadth-first search algorithm, is the space complexity $O (b^d)$, where $b$ is the branching factor and $d$ the length of the optimal path (assuming
Why do we use a last-in-first-out queue in depth-first search? We use the LIFO queue, i e stack, for implementation of the depth-first search algorithm because depth-first search always expands the deepest node in the current frontier of the search tree Norvig and Russell write in section 3 4 3 The search proceeds immediately to the deepest level of the search tree, where the nodes have no successors As those nodes are expanded, they are dropped from