Theresa Swift

LO
h-index42
3papers
Novelty22%
AI Score28

3 Papers

11.4PLMar 31
Multi-paradigm Logic Programming in the ${\cal E}$rgoAI System

Michael Kifer, Theresa Swift

ErgoAI is a high level, multi-paradigm logic programming language and system developed by Coherent Knowledge Systems as an enhancement of and a successor to the popular Flora-2 system. ErgoAI is oriented towards scalable knowledge representation and reasoning, and can exploit both structured knowledge as well as knowledge derived from external sources such as vector embeddings. From the start, ErgoAI (and Flora-2 before it) were designed to exploit the well-founded semantics for reasoning in a multi-paradigm environment, including object-based logic (F-logic) with non-monotonic inheritance; higher order syntax in the style of HiLog; defeasibility of rules; semantically clean transactional updates; extensive use of subgoal delay for handling unsafe queries and for better performance; and optional support for bounded rationality at a module level. Although Flora-2 programs are compiled into XSB and adopt many Prolog features, ErgoAI is altogether a different language and system. Under consideration in Theory and Practice of Logic Programming (TPLP).

LOJul 23, 2025
Integrating Belief Domains into Probabilistic Logic Programs

Damiano Azzolini, Fabrizio Riguzzi, Theresa Swift

Probabilistic Logic Programming (PLP) under the Distribution Semantics is a leading approach to practical reasoning under uncertainty. An advantage of the Distribution Semantics is its suitability for implementation as a Prolog or Python library, available through two well-maintained implementations, namely ProbLog and cplint/PITA. However, current formulations of the Distribution Semantics use point-probabilities, making it difficult to express epistemic uncertainty, such as arises from, for example, hierarchical classifications from computer vision models. Belief functions generalize probability measures as non-additive capacities, and address epistemic uncertainty via interval probabilities. This paper introduces interval-based Capacity Logic Programs based on an extension of the Distribution Semantics to include belief functions, and describes properties of the new framework that make it amenable to practical applications.

LOFeb 11, 2025
Proceedings 40th International Conference on Logic Programming

Pedro Cabalar, Francesco Fabiano, Martin Gebser et al.

Since the first conference In Marseille in 1982, the International Conference on Logic Programming (ICLP) has been the premier international event for presenting research in logic programming. These proceedings include technical communications about, and abstracts for presentations given at the 40th ICLP held October 14-17, in Dallas Texas, USA. The papers and abstracts in this volume include the following areas and topics. Formal and operational semantics: including non-monotonic reasoning, probabilistic reasoning, argumentation, and semantic issues of combining logic with neural models. Language design and programming methodologies such as answer set programming. inductive logic programming, and probabilistic programming. Program analysis and logic-based validation of generated programs. Implementation methodologies including constraint implementation, tabling, Logic-based prompt engineering, and the interaction of logic programming with LLMs.