http://dl.gi.de/handle/20.500.12116/36217 2026-07-23T18:36:27Z http://dl.gi.de/handle/20.500.12116/36249 Cognitive Argumentation for Human Syllogistic Reasoning Saldanha, Emmanuelle-Anna Dietz; Kakas, Antonis This paper brings together work from the psychology of reasoning and computational argumentation in AI to propose a cognitive computational model for human reasoning and in particular for human syllogistic reasoning. The model is grounded in the formal framework of argumentation in AI with its dialectic semantics for the quality of arguments. Arguments for logical conclusions are constructed via a set of proposed argument schemes, chosen for their cognitive validity, as supported by studies in cognitive psychology. The proposed model with its cognitive principles of argumentation can encompass together in a uniform way both formal and informal logical reasoning, capturing well the empirical data of human syllogistic reasoning in the recent Syllogism Challenge 2017 on cognitive modeling. The paper also argues that the proposed approach could be applied more generally to other forms of high-level human reasoning. 2019-01-01T00:00:00Z http://dl.gi.de/handle/20.500.12116/36246 Semantics of Analogies from a Logical Perspective Abdelfattah, Ahmed M. H.; Krumnack, Ulf A number of different approaches to model analogies and analogical reasoning in AI have been proposed, applying different knowledge representation and mapping strategies. Nevertheless, analogies still seem to be hard to grasp from a formal perspective, with no known treatment in the literature of, in particular, their formal semantics, though the empirical treatments involving human subjects are abundant. In this paper we present a framework that allows to analyze the syntax and the semantics of analogies in a universal logic-based setting without committing ourselves to a specific type of logic. We show that the syntactic process of analogy-making by finding a generalization can be given a sensible interpretation on the semantic level based on the theory of institutions . We then apply these ideas by considering a framework of analogy-making that is based on classical first-order logic. 2019-01-01T00:00:00Z http://dl.gi.de/handle/20.500.12116/36244 Thinking is Founded on Models of Possibilities Ragni, Marco 2019-01-01T00:00:00Z http://dl.gi.de/handle/20.500.12116/36245 Image Schema Combinations and Complex Events Hedblom, Maria M.; Kutz, Oliver; Peñaloza, Rafael; Guizzardi, Giancarlo Formal knowledge representation struggles to represent the dynamic changes within complex events in a cognitively plausible way. Image schemas, on the other hand, are spatiotemporal relationships used in cognitive science as building blocks to conceptualise objects and events on a high level of abstraction. In this paper, we explore this modelling gap by looking at how image schemas can capture the skeletal information of events and describe segmentation cuts essential for conceptualising dynamic changes. The main contribution of the paper is the introduction of a more systematic approach for the combination of image schemas with one another in order to capture the conceptual representation of complex concepts and events. To reach this goal we use the image schema logic ISL , and, based on foundational research in cognitive linguistics and developmental psychology, we motivate three different methods for the formal combination of image schemas: merge, collection, and structured combination. These methods are then used for formal event segmentation where the changes in image-schematic state generate the points of separation into individual scenes. The paper concludes with a demonstration of our methodology and an ontological analysis of the classic commonsense reasoning problem of ‘cracking an egg.’ 2019-01-01T00:00:00Z