We talked about "forward-chaining" vs. "backward chaining" expert systems. Here's a little more explanation.

Forward chaining--data-driven inference strategy in which the system begins with known data and works forward to see if any conclusions can be drawn.

Backward chaining--goal-driven inference strategy in which the system works backward from the goal to find supporting data; working "backward" through a chain of rules in an attempt to find a verifiable set of condition clauses.

Also, here's a little table that should help:

cheers...Jim