2026-05-23T04:30:44.864Z http://ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai

ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai:2:7615 2020-02-03T09:34:46Z 2

Putting the Human Back in the Loop: A Study in Human-Machine Cooperative Learning 2020 http://ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai/record/2/7615 http://www.uni-obuda.hu/journal/Gnjatovic_Macek_Adamovic_99.pdf M. Gnjatović N. Maček S. Adamović This paper1 introduces a novel approach to human-machine collaborative learning that allows for the chronically missing human learnability in the context of supervised machine learning. The basic tenet of this approach is the refinement of a human designed software model through the iterative learning loop. Each iteration of the loop consists of two phases: (i) automatic data-driven parameter adjustment, performed by means of stochastic greedy local search, and (ii) human-driven model adjustment based on insights gained in the previous phase. The proposed approach is demonstrated through a real-life study of automatic electricity meter reading in the presence of noise. Thus, a cognitively-inspired non-connectionist approach to digit detection and recognition is introduced, which is subject to refinement through the iterative process of human-machine cooperation. The evaluation of the prototype system is reported. article 17 2 191 210 1785-8860 Acta Polytechnica Hungarica