The four categories of Artificial Intelligence, based on how intelligent systems are designed to think or act, can be described as follows:
1. Systems that Think Like Humans
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These systems try to mimic the human thought process.
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The focus is on cognitive modeling — understanding how humans think through psychological experiments and cognitive science.
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Example: AI models that simulate human decision-making, learning, or problem-solving processes.
2. Systems that Act Like Humans
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These aim to replicate human behavior, passing the Turing Test.
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They include capabilities like:
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Natural Language Processing (understanding human language)
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Knowledge Representation (storing and managing information)
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Automated Reasoning (using knowledge to make decisions)
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Machine Learning, Computer Vision, and Robotics (for adaptive learning, visual perception, and movement).
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3. Systems that Think Rationally
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These systems follow the “laws of thought”, attempting to make logically correct decisions.
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Inspired by formal logic (e.g., Aristotle’s syllogism), they aim to reason deductively.
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Challenges:
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Hard to translate vague human knowledge into formal logic.
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Real-world problems can become computationally intensive.
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4. Systems that Act Rationally
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These systems focus on behaving in ways that maximize goal achievement — the “rational agent” model.
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Rational behavior is not about copying human thinking but about making the best possible decision given the available information.
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Advantage: More flexible and scientifically extendable than purely logic-based systems.