Managing Uncertainty in AI and Cognitive Computing
Understanding Uncertainty in Artificial Intelligence
Uncertainty arises when we are not 100% sure about the outcome of decisions. It appears in cases where conditions are neither completely true nor completely false.
Sources of Uncertainty in AI
- Uncertain Data: Occurs when data is missing, noisy, inconsistent, ambiguous, or based on expert guesses.
- Uncertain Knowledge: Occurs when knowledge has multiple causes/effects or causality is incomplete.
Reasons for Uncertainty
- Partially observable environments: For example, hidden cards in a game.
- Dynamic environments: Such as rapidly changing technology.
- Incomplete agent knowledge: For example, unpredictable consequences.
- Inaccessible environments: Such as unseen global events.
Ways to Handle Uncertainty
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