Cause-effect relation is represented in the main memory by cause-effect relation table.
“Sun” is a cause for “heat”.
“Fire” is a cause for “heat”.
“Sun” is a cause for “sunburn”.
So, there are 3 cause-effect relations in this example:
See large-scale model here: Cause-effect graph
Cause-effect relations are so important because:
1) Cause-effect relations help to understand what would happen as a result of current situation. Cause effect relations help to predict the future of current context.
In order to find out what would happen, strong AI should just find all effect concepts for specified concepts.
2) Cause-effect relations help to understand what strong AI can do in order to achieve some goals.
Example (based on diagram above):
1) Let imagine that strong AI wants to find out what would be the result of the sun. In order to figure that out, strong AI would take a look into cause-effect relations and find out that probable results are “Heat” and “SunBurn”.
2) Let’s imagine that current goal of strong AI is “Heat”. In order to achieve this goal strong AI should follow cause-effect relation in reverse direction and find out that “Fire” and “Sun” concepts could help to achieve the current goal “Heat”.