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Uncertainty: Probability and Markov Chains, AI often works in environments…
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- AI often works in environments where outcomes are unpredictable or unknown. Agents need to make good decisions even without full information.
A rational agent makes the best possible choice based on current knowledge, expected outcomes, and probabilities.
In diagnosis tasks, an AI must consider multiple possible causes for observed symptoms, each with a probability.
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- Combines probabilities with preferences to help agents make the best possible choices.
A system that evolves over time with some level of randomness. Used to model uncertainty that unfolds step by step.
- Used in text prediction, board games, weather models.
- Chaos theory studies systems that are deterministic but extremely sensitive to initial conditions — appearing random.
- Markov Chains were named after Russian mathematician Andrey Markov, who introduced this theory in the early 1900s.
