Final answer:
Means-end analysis is a strategy that can apply forwards and backwards search in problem-solving, used in AI and cognitive psychology to handle complex problems by breaking them into simpler sub-problems.
Step-by-step explanation:
The statement is true: means-end analysis can indeed involve both forwards and backwards search. Means-end analysis is a problem-solving strategy used in artificial intelligence (AI) and cognitive psychology. It involves breaking down the difference between the current state and the goal state into smaller, more manageable differences, selecting actions that reduce these differences.
In forward search, the approach starts from the initial state and moves toward the goal state by considering actions that lead to states closer to the goal. Conversely, in backward search, the process begins from the goal state and moves backwards to find actions that could lead to that state from the initial state. This method allows problem solvers to work on sub-problems that lead them incrementally closer to solving the main problem.