We have 2 of 6 papers
We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.
Not the right person? Other researchers publish under this name.
A multi-stage rule-chaining framework that performs compositional reasoning across symbolic, structural, and conceptual levels and suggests that rule chaining and hierarchical composition can advance machine reasoning toward transparent, human-aligned abstraction without relying on task-specific tuning.
ORDDAR (Observation-Driven Reasoning for Distortion-Resilient Decision, Action, and Cognitive Recovery) is presented, a reasoning framework that models reasoning as cognitive state transitions, detects localized distortions, retrieves related reasoning from prior experiences, and repairs only the affected states.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
