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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
Why is A* optimal if the heuristic function is admissible? 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 the cost of its successor, n′ n ′, plus the successor's heuristic value Why is A*, using tree or graph searches, optimal, if it uses an admissible heuristic?
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
What is the space complexity of breadth-first search? The space complexity of the breadth-first search algorithm is O(bd O (b d) in the worst case, and it corresponds to the largest possible number of nodes that may be stored in the frontier at once, where the frontier is the set of nodes (or states) that you are currently considering for expansion You can take a look at section 3 5 (page 74) of the book Artificial Intelligence: A Modern
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?
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
philosophy - Can the first emergence of consciousness in evolution be . . . Current limitations in our knowledge mean that the question is not directly answerable: 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