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
A* and uniform-cost search are apparently incomplete You forgot to calculate and take into account the costs of the actual paths You forgot to accumulate the cost of the edges for going forward and backward multiple times!
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)
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
comparison - When should I use Genetic Algorithms as opposed to . . . The paper Comparison between genetic algorithms and particle swarm optimization (1998, by Eberhart and Shi) does not really answer the question of when to use one over the other (this may be an open question), but at least it provides a comparison of how the methods work and what could affect their performance (i e which parameters or operators they use, and what the typical values are), so
What is the space complexity of breadth-first search? Stack Exchange Network Stack Exchange network consists of 183 Q A communities including Stack Overflow, the largest, most trusted online community for developers to learn, share their knowledge, and build their careers
How does the uniform-cost search algorithm work? Uniform Cost Search is also called the Cheapest First Search For an example and entire explanation you can directly go to this link: Udacity - Uniform Cost Search
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