Artificial Intelligence, Situated Approach
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High Quality Content by WIKIPEDIA articles! After several decades of success, traditional artificial intelligence approaches to modeling decision-making, such as expert systems, finite state machines or decision trees reached their limitations in the 1980s when researchers tried to use them to drive real robots in uncertain environments. In fact, classical AI technologies face intractable issues, such as combinatorial explosion, when confronted with real-world modeling problems, and several directions have been explored by researchers to address these issues. All these approaches focus on…mehr

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High Quality Content by WIKIPEDIA articles! After several decades of success, traditional artificial intelligence approaches to modeling decision-making, such as expert systems, finite state machines or decision trees reached their limitations in the 1980s when researchers tried to use them to drive real robots in uncertain environments. In fact, classical AI technologies face intractable issues, such as combinatorial explosion, when confronted with real-world modeling problems, and several directions have been explored by researchers to address these issues. All these approaches focus on modeling intelligence situated in a given environment: they have come to be known as the situated approach to AI.