🤖 AI Summary
This work addresses the challenge of scalable representation and reasoning in multi-paradigm environments that integrate structured knowledge with external knowledge sources, such as vector embeddings. To this end, the paper proposes ErgoAI, a novel high-level logic programming system grounded in well-founded semantics. ErgoAI unifies several advanced mechanisms—including F-logic object-oriented reasoning, HiLog higher-order syntax, defeasible rules, transactional updates, and subgoal tabling—while supporting module-level bounded rationality and non-monotonic inheritance. Compared to Flora-2 and Prolog, ErgoAI significantly enhances expressiveness and inference efficiency in complex knowledge-intensive settings without compromising semantic rigor.
📝 Abstract
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).