Applying Lakatos-style reasoning to AI problems

Applying Lakatos-style reasoning to AI problems

One current direction in AI research is to focus on combining different reasoning styles such as deduction, induction, abduction, analogical reasoning, non-monotonic reasoning, vague and uncertain reasoning. The philosopher Imre Lakatos produced one such theory of how people with different reasoning styles collaborate to develop mathematical ideas. Lakatos argued that mathematics is a quasi-emp...

Lakatos-style Methods in Automated Reasoning

Lakatos-Style Automated Theorem Modification

We describe a flexible approach to automated reasoning, where non-theorems can be automatically altered to produce proved results which are related to the original. This is achieved through an interaction of the HR machine learning system, the Otter theorem prover and the Mace model generator, and uses methods inspired by Lakatos’s philosophy of mathematics. We demonstrate the effectiveness of ...

Working Group in Model-Based Design and Reasoning. Part II: Design

Conventional Artiicial Intelligence techniques such as expert systems have often been found to be too brittle for large-scale applications. Model-based reasoning is a technique for making Artiicial Intelligence software applicable to problems of realistic size. In this working group, we have investigated some fundamental issues in model-based reasoning and various applications in diagnosis, con...

Anchored Narratives in Reasoning about Evidence

This paper concerns the reasoning with stories, evidence and generalisations in a legal context. We will make some notions from the existing Anchored Narratives theory more clear by making use of two formal techniques from AI, namely causal-abductive reasoning and default-style argumentation. We will propose a combination of these two formalisms which solves some of the problems of the causal-a...