Default reasoning in AI is like making educated guesses when you don't have all the information you need. Default reasoning in artificial intelligence (AI) allows systems to make plausible assumptions and conclusions in situations with incomplete or uncertain information.
By relying on typical or "default" knowledge, such as assuming birds can fly unless specified otherwise, AI systems can function effectively in the real world where perfect information is rare. This type of reasoning is non-monotonic, meaning new information can change previously drawn conclusions, and it employs methods like circumscription and default logic to manage assumptions.
Default reasoning is crucial for handling uncertainty, enhancing flexibility, and improving efficiency in AI, though it faces challenges like conflict resolution and integrating with other reasoning methods.
Key aspects of Default Reasoning are:
Default Rules: These are common-sense assumptions you usually make. For example, "Most birds can fly."
Exceptions: Sometimes, there are special cases that don't follow the usual rules. For example, penguins are birds, but they can't fly.
Changing Your Mind: If you learn something new that contradicts your assumption, you change your guess. For instance, if you first assume a bird can fly but then find out it's a penguin, you update your guess to say it can't fly.
Handling Missing Information: Even if you don't know everything, you can still make a good guess based on what you typically know. So, if you see a bird and don't know what kind it is, you might guess it can fly because most birds do.