OntoAgentic AI
Our paradigm for building intelligent agents that combine deep semantic understanding with explicit knowledge representation. OntoAgentic AI integrates ontological world models, cognitive architectures, and hybrid neuro-symbolic processing to create agents that truly understand language, reason about goals, and explain their decisions. This approach prioritizes meaning over pattern matching, enabling trustworthy AI that humans can inspect and verify.
Content-Centric Cognitive Modeling
Large-scale knowledge bases integrated with perception, reasoning, and action. Our approach emphasizes meaning - the deep, context-sensitive understanding humans achieve naturally.
Cognitive Robotics
Robotic systems that reason about joint goals, explain their actions, and collaborate with humans. HARMONIC is our flagship cognitive-robotic architecture for human-robot teaming.
Hybrid AI Systems
Combining knowledge-based processing with machine learning in a symbolic-first paradigm. LLMs serve as tools within our cognitive framework for fluent language with rigorous grounding.
Explainable AI
Transparency and explainability are central to our work. Our agents justify their actions in human-understandable terms, supporting trust in high-stakes collaborative settings.