Artificial Intelligence is mimicking cognitive abilities. All sorts of behaviour we deem intelligent are being scrutinised and implemented in some way or another. Some more successfully so than others. Experience re-use is one of the successful approaches.
Experience guides us in our learning efforts and is one of the most important assets for problem solving. Experience is everywhere. For example, a recording technician needs experience in the studio to produce a recording worth listening to. Does the recording sound full and rich or still too tinny? Does the bass section sound overwhelming? A completely different field is gold ore mining. Lots of experience with mining and extracting the valuable metal has been published and even more specific knowledge resides in experts’ heads. For both domains holds that past experience — my own or someone else’s — can help me solve a current problem, for example, in the recording studio or when planning a new mining operation. Case-based reasoning, a methodology in which experience is expressed in the form of problem-solution pairs called cases, allows transferring and applying expert knowledge where needed.
Experience re-use can also be a means of personalisation, for example, in social media applications. Someone else’s similar context might improve my own user experience. The list is seemingly endless.
Thomas Roth-Berghofer, Professor of Artificial Intelligence at the University of West London, is giving a talk on this topic at the Technology and Innovation Conference Techsylvania in Cluj-Napoca, Romania, on 8 June 2015.