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Specifying Search ProblemsIn our agent expressions, a problem to be solved is a specific task where the agent starts with the atmosphere in a given state and acts upon the environment pending the altered state has some programmed excellence. The set of states which are possible via some series of actions the agent takes is called the search space. The sequence of actions that the agent actually performs is its search path, and the last state is a solution if it has the necessary assets. There may be many solutions to a particular trouble. If you can think of the task you want your agent to do in these terms, then you will need to mark a problem solving agent which uses search.It is important to recognize the scope of your task in conditions of the problems which will require to be solved. For instance, there are some errands which are solo problems solved by penetrating, e.g., find a route on a map. Alternatively, there are tasks such as charming at chess, which have to be out of order down into sub-problems (searching for the best move at each stage). Other tasks can be achieved without searching whatsoever e.g., multiplying two big numbers together - you wouldn't vision of searching through the figure line until you came crossways the answer!There are three first considerations in problem solving (as described in Russell and Norvig):
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I am using block matching algorithm to get the motion vectors, now, how can I get the depth map/depth value from the motion vectors?
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