Try this exercise. Fill in the missing part by typing it in.

One optimization of the A algorithm is the bidirectional A search. Instead of performing the search from the start node to the goal node, bidirectional A* search performs two simultaneous searches: one from the start node and one from the goal node. The algorithm continues until the searches meet in the middle or the open set becomes empty. This can greatly reduce the number of nodes that need to be explored and lead to faster pathfinding.

Another optimization technique is Jump Point Search which reduces the number of nodes explored by identifying specific points in the grid, known as jump points. Instead of expanding all neighboring nodes, Jump Point Search jumps over certain areas in the grid, improving the algorithm's performance.

Theta Search is a variant of the A algorithm that allows for smoother paths by considering the line of sight between nodes. Instead of following the exact grid-based path, Theta* Search looks for intermediate points in the line of sight and uses them to create a more continuous path.

One variant of the A algorithm is the _ algorithm, which is a heuristic search algorithm that combines the Dijkstra's algorithm and A algorithm. It uses a bidirectional search approach and also incorporates an additional heuristic, known as a potential function, to guide the search towards the goal node. The potential function assigns a score to each node based on its estimated distance to the goal, and the algorithm selects the node with the lowest potential function score at each step.