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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
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!
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
Which courses in computer science and logic are relevant to Machine . . . optionally, courses in logic, but be aware that this is almost a fringe area in AI now, and essentially irrelevant to a PhD in machine learning The parts you need are usually covered in a broad survey AI course These courses give you the basic mathematical fluency to understand most machine learning algorithms well
philosophy - Can the first emergence of consciousness in evolution be . . . There is no scientific consensus on what consciousness is Therefore any device designed to "be conscious" is necessarily going to be built on the premise of unsupported, maybe fringe, theory There is no robust measure of consciousness If any AI system was built in order to exhibit conscious behaviour, there would be no way to prove it is
norvig russell - What does the statement with the max do in the . . . By taking the max, the code ensures that states that are restored maintain at least the cost of the previously best unexpanded state (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 )