Modeling the suppression task under weak completion and well-founded semantics

Formal approaches that aim at representing human reasoning should be evaluated based on how humans actually reason. One way in doing so, is to investigate whether psychological findings of human reasoning patterns are represented in the theoretical model. The computational logic approach discussed here is the so called weak completion semantics which is based on the three-valued Lukasiewicz logic. We explain how this approach adequately models Byrne’s suppression task, a psychological study where the experimental results show that participants’ conclusions systematically deviate from the classical logically correct answers. As weak completion semantics is a novel technique in the field of Computational Logic, it is important to examine how it corresponds to other already established non-monotonic approaches. For this purpose we investigate the relation of weak completion with respect to completion and three-valued stable model semantics. In particular, we show that well-founded semantics, a widely accepted approach in the field of non-monotonic reasoning, corresponds to weak completion semantics for a specific class of modified programs.