tailieunhanh - Notes 10: Learning from observations

Notes 10: Learning from observations presents about Learning agents, Inductive learning, Decision tree learning, Learning element, Inductive learning method, Learning decision trees, Attribute-based representations. | Notes 10: Learning from observations ICS 171 Fall 2006 () Outline • Learning agents • Inductive learning • Decision tree learning Learning • Learning is essential for unknown environments, – ., when designer lacks omniscience • Learning is useful as a system construction method, – ., expose the agent to reality rather than trying to write it down • Learning modifies the agent's decision mechanisms to improve performance Learning agents Learning element • Design of a learning element is affected by – Which components of the performance element are to be learned – What feedback is available to learn these components – What representation is used for the components • Type of feedback: – Supervised learning: correct answers for each example – Unsupervised learning: correct answers not given – Reinforcement learning: occasional .

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