AO* search
Key Concepts: (copy)
AdvantagesAllows for anytime performance: Provides a solution at any point during the search, improving over time. Guarantees optimality under certain conditions (admissible heuristic). Efficiently prunes the search space by focusing on nodes with promising cost estimates. |
WorkingThe evaluation function in AO* looks like this: f(n) = g(n) + h(n) f(n) = The actual cost of traversal. g(n) = the cost from the initial node to the current node. h(n) = estimated cost from the current node to the goal state. ComplexityThe time complexity of AO* depends on factors such as the branching factor, the quality of the heuristic function, and the termination condition. In the worst case of an unbounded search space, the number of nodes expanded is exponential in the depth of the solution (the shortest path) d: O(b^d), where b is the branching factor Application1.Path planning in robotics and artificial intelligence. 2.Game AI for decision-making and pathfinding. 3.Logistics and transportation route optimization. 4.Automated planning and scheduling problems. |
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AO* Search Cheat Sheet (DRAFT) by creedorian
AO* Search Algorithm Cheatsheet
This is a draft cheat sheet. It is a work in progress and is not finished yet.