Transportability of Causal and Statistical Relations: A Formal Approach

We address the problem of transferring information learned from experiments to a different environment, in which only passive observations can be collected. We introduce a formal representation called “selection diagrams” for expressing knowledge about differences and commonalities between environments and, using this representation, we derive procedures for deciding whether effects in the target environment can be inferred from experiments conductedelsewhere. When the answeris affirmative, the proceduresidentify the set of experiments and observations that need be conducted to license the transport. We further discuss how transportability analysis can guide the transfer of knowledge in non-experimental learning to minimize re-measurement cost and improve prediction power.

• Type: Journal
• Year: 2011
• Where: AAAI
• Authors: Judea Pearl, Elias Bareinboim
• Keywords: AAAI 2011, Commonalities, Formal Representation, Intelligent Agents, Target Environment