Propositional Defeasible Explanation

Honours Project in Knowledge Representation and Reasoning

By: Lloyd Everett, Emily Morris

Knowledge Representation and Reasoning is a field within AI in which information and reasoning is modeled using formal logic. In classical logics, we can use entailment to infer new information from our modeled information. Explanations provide a...

Centre for Artificial Intelligence Research

Defeasible Reasoning for Datalog

Integrating rules with exceptions into Datalog ontologies.

By: Guy Paterson-Jones

Supervised By: Tommie Meyer

Datalog is an expressive database query language based on the logic programming paradigm, meaning that its queries can be interpreted in terms of mathematical formulas in classical first-order logic. Recently, extensions of Datalog have been...

CS Masters by Dissertation Centre for Artificial Intelligence Research

Human Belief Change

An Empirical Investigation for Patterns of Belief Change in Human Reasoning

By: Clayton Baker

Belief revision and belief update are approaches to represent and reason with knowledge in artificial intelligence. Previous empirical studies showed that human reasoning is consistent with non-monotonic logic. Additionally, previous studies showed...

CS Masters by Dissertation CS PhD Centre for Artificial Intelligence Research

SCADR

An Investigation into the Scalability of Defeasible Reasoning

By: Joel Hamilton, Daniel Park, Aidan Bailey

Knowledge representation and reasoning (KRR) is an approach to artificial intelligence (AI) in which a system has some information about the world represented formally (a knowledge base), and is able to reason about this information. Defeasible...

Centre for Artificial Intelligence Research