Agents who apply problem solving methods usually use state representations on which approximate solution search procedures are built, which are not always optimal, but have a sufficient quality for the time and computing resources available. Students will know and know how to apply the most common general-purpose algorithms and heuristics to solve search problems with state representations, both through uninformed strategies and based on some approximate knowledge of the problem (informed search). More complex contexts that condition these strategies will also be dealt with, such as the existence of adversaries or restrictions in the search process. The course will also address planning algorithms in the field of Artificial Intelligence.
(*)The teaching guide is the document in which the URV publishes the information about all its courses. It is a public document and cannot be modified. Only in exceptional cases can it be revised by the competent agent or duly revised so that it is in line with current legislation.
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