Multi-paradigm Logic Programming in the ${\cal E}$rgoAI System
This work addresses the need for advanced logic programming tools in AI and knowledge representation, but it appears incremental as an enhancement of an existing system.
The paper introduces ErgoAI, a multi-paradigm logic programming system designed for scalable knowledge representation and reasoning, building upon the Flora-2 system with enhancements like support for external knowledge sources and various semantic features.
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).