A framework for arguing from analogy: preliminary results
Guillermo R Simari
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Abstract
Human reasoning applies argumentation patterns to draw conclusions about a particular subject. These patterns represent the structure of the arguments in the form of argumentation schemes which are useful in AI to emulate human reasoning. A type of argument schema is that what allow to analyze the similarities and differences between two arguments, to find a solution to a new problem from an already known one. Researchers in the heavily studied field of analogies in discourse have recognized that there is not a full and complete definition to indicate when two arguments are considered analogous. Our proposal presents an initial attempt to formalize argumentation schemes based on analogies, considering a relationship of analogy between arguments. This will contribute to the area increasing such schemes usefulness in Artificial Intelligence (AI), since it can be implemented later in Defeasible Logic Programming (DeLP).
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ISSA Conference Proceedings , 2023
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Argumentation schemes in AI: A literature review. Introduction to the special issue
Argument & Computation, 2021
Argumentation schemes [35,80,91] are a relatively recent notion that continues an extremely ancient debate on one of the foundations of human reasoning, human comprehension, and obviously human argumentation, i.e., the topics. To understand the revolutionary nature of Walton's work on this subject matter, it is necessary to place it in the debate that it continues and contributes to, namely a view of logic that is much broader than the formalistic perspective that has been adopted from the 20th century until nowadays. With his book Argumentation schemes for presumptive reasoning, Walton attempted to start a dialogue between three different fields or views on human reasoning-one (argumentation theory) very recent, one (dialectics) very ancient and with a very long tradition, and one (formal logic) relatively recent, but dominating in philosophy. Argumentation schemes were proposed as dialectical instruments, in the sense that they represented arguments not only as formal relations, but also as pragmatic inferences, as they at the same time depend on what the interlocutors share and accept in a given dialogical circumstance, and affect their dialogical relation. In this introduction, the notion of argumentation scheme will be analyzed in detail, showing its different dimensions and its defining features which make them an extremely useful instrument in Artificial Intelligence. This theoretical background will be followed by a literature review on the uses of the schemes in computing, aimed at identifying the most important areas and trends, the most promising proposals, and the directions of future research.
An Approach to the Semantics of Analogical Relations1
2007
Whereas approaches for deductive and inductive reasoning are well-examined for decades, analogical reasoning seems to be a hard problem for machine intelligence. Although several models for computing analogies have been proposed, there is no uncontroversial theory of the semantics of analogies. In this paper, we will investigate semantic issues of analogical relations, in particular, we will specify a model theory of analogical transfers. The presented approach is based on Heuristic-Driven Theory Projection (HDTP) a framework that computes an analogical relation between logical theories describing a source and a target domain. HDTP establishes the analogy by an abstraction process in which formulas from both domains are generalized creating a theory that syntactically subsumes the original theories. We will show that this syntactic process can be given a sensible interpretation on the semantic level. In particular, given models of the source and the target domains, we will examine t...
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2008
Human-level reasoning is manifold and comprises a wide variety of different reasoning mechanisms. So far, artificial intelligence has focused mainly on using the classical approaches deduction, induction, and abduction to enable machines with reasoning capabilities. However, the approaches are limited and do not reflect the mental, cognitive process of human reasoning very well. We contend that analogical reasoning is the driving force behind human thinking and therefore propose analogy as an integrating framework for the variety of human-level reasoning mechanisms.
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In this paper, it is shown (1) that there are two schemes for argument from analogy that seem to be competitors but are not, (2) how one of them is based on a distinctive type of similarity premise, (3) how to analyze the notion of similarity using story schemes illustrated by some cases, (4) how arguments from precedent are based on arguments from analogy, and in many instances arguments from classification, and (5) that when similarity is defined by means of story schemes, we can get a clearer idea of how it integrates with the use of argument from classification and argument from precedent in case-based reasoning by using a dialogue structure.
A Logical Approach to Reasoning
by Analogy.
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A Formal Definition and a Sound Implementation of Analogical Reasoning in Logic Programming
2000
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Introducing a Context-Aware Scheme in an intelligent reasoning process
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A Multi-Strategy Approach to Structural Analogy Making
Journal of Intelligent Information Systems, 2017
Analogy is the cognitive process of matching the characterizing features of two different items. This may enable reuse of knowledge across domains , which can help to solve problems. Indeed, abstracting the 'role' of the features away from their specific embodiment in the single items is fundamental to recognize the possibility of an analogical mapping between them. The analogical reasoning process consists of five steps: retrieval, mapping, evaluation , abstraction and re-representation. This paper proposes two forms of an operator that includes all these elements, providing more power and flexibility than existing systems. In particular, the Roles Mapper leverages the presence of identical descriptors in the two domains, while the Roles Argumentation-based Mapper removes also this limitation. For generality and compliance with other reasoning operators in a multi-strategy inference setting, they exploit a simple formalism based on First-Order Logic and do not require any background knowledge or meta-knowledge. Applied to the most critical classical examples in the literature, they proved to be able to find insightful analogies.
Arguments by Analogy (and What We Can Learn about Them from Aristotle)
Argumentation Library, 2015
The paper contributes to the debate about arguments by analogy, especially the distinction between 'deductive' and 'inductive' analogies and the question how such arguments can be 'deductive', yet nonetheless defeasible. It claims that 'deductive' and 'inductive' are structural, not normative categories, and should not be used to designate argument validity. Based on Aristotle's analysis of enthymemes, examples, and metaphors, it argues that arguments from analogy are complex arguments that involve inductive, abductive, and deductive components.
REASONING BY ANALOGY
Analogy plays an important role in science as well as in non-scientific domains such as taxonomy or learning. We make explicit the difference and complementarity between the concept of analogical statement, which merely states that two objects have a relevant similarity, and the concept of analogical inference, which relies on the former in order to draw a conclusion from some premises. For the first, we show that it is not possible to give an absolute definition of what it means for two objects to be analogous; a relative definition of analogy is introduced, only relevant from some point of view. For the second, we argue that it is necessary to introduce a background over-hypothesis relating two sets of properties; the belief strength of the conclusion is then directly related to the belief strength of the over-hypothesis. Moreover, we assert the syntactical identity between analogical inference and one case induction despite important pragmatic differences.
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