Heuristic search is a method of problem-solving that uses a specific set of rules or “heuristics” to guide the search for a solution. In inductive learning, the heuristic search can be used to search for the most likely hypothesis or model that explains a given set of data. This can be done by using heuristics to guide the search through the space of possible hypotheses and evaluating each hypothesis based on how well it fits the data. Heuristic search can be useful in inductive learning because it can help to find a good hypothesis quickly, even when the space of possible hypotheses is large and complex.
There are several techniques that can be used to optimize the complexity of a hypothesis during a heuristic search in inductive learning:
Occam’s Razor:
This principle states that, given a set of competing hypotheses, the simplest hypothesis that explains the data is the most likely to be true. This can be used to guide the search by favoring simpler…