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Forward vs backward chaining
Short answer
Forward chaining is data-driven, starting from facts and firing rules to reach a goal, possibly deriving irrelevant facts. Backward chaining is goal-driven, starting from the goal and working backward to find supporting facts; it is focused but may loop.
Differentiate between forward chaining and backward chaining.
Both are inference methods for rule-based systems with IF-THEN rules.
| Basis | Forward chaining | Backward chaining |
|---|---|---|
| Direction | From known facts towards the goal (bottom-up) | From the goal back to facts (top-down) |
| Approach | Data-driven: fires rules whose conditions are satisfied, adding new facts | Goal-driven: finds rules whose conclusion matches the goal and tries to prove their conditions as sub-goals |
| Start | Facts / initial data | Hypothesis / goal to prove |
| Strategy | Breadth-first like | Depth-first like |
| Efficiency | May derive many irrelevant facts | Focuses only on rules relevant to the goal |
| Best for | Monitoring, planning, design, interpretation (many conclusions from data) | Diagnosis, answering a specific query (few goals) |
| Example systems | OPS5, XCON | MYCIN, Prolog |
| Termination | Stops when no new facts or goal is derived | Stops when the goal is proved or no rules remain |
✓ Answer checked by Claude Opus 5.5 (high effort)
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