Can Formal Non-monotonic Systems Properly Describe Human Reasoning?

Gregory KuhnmuenchU Freiburg
Marco RagniUniversity of Freiburg

Abstract

Monotonic (logical) reasoning makes the strong claim that an inference cannot be contradicted by future information; an assumption contrary to everyday life experience. This assumption is relaxed in non-monotonic reasoning. However, there are only few formal non-monotonic theories of reasoning that have inspired psychological theory-building. Can formal systems such as cumulative logic (system C) or preferential logic (system P), developed in philosophy and artificial intelligence, predict human non-monotonic inferences? Previous investigations have mainly used probabilistic representations of these systems and it remains unclear whether participants make the same inferences based on a qualitative description. We describe a different methodological approach and report related experimental findings that run counter to current approaches to human non- monotonic reasoning. Implications of our proposed method are discussed.

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