A teaching methodology called Imitative-Reinforcement-Corrective (IRC) learning is described, and proposed as a general approach for teaching embodied non-linguistic AGI systems. I...
Ben Goertzel, Cassio Pennachin, Nil Geisweiller, M...
Every agent aspiring to human level intelligence, every AGI agent, must be capable of a theory of mind. That is, it must be able to attribute mental states, including intentions, t...
We give a brief overview of the main characteristics of diagrammatic reasoning, analyze a case of human reasoning in a mastermind game, and explain why hybrid representation system...
Human brain is exceptionally complex and simple at the same time. Its extremely composite biological structure results itself in human everyday behavior that many people might cons...
In order to claim fully general intelligence in an autonomous agent, the ability to learn is one of the most central capabilities. Classical machine learning techniques have had ma...
Abstract. An artificial system that achieves human-level performance on opendomain tasks must have a huge amount of knowledge about the world. We argue that the most feasible way t...
. We consider the Distributed Cognition paradigm as a framework for implementing artificial components of human cognition. We take email/internet search as a setting of distributed...
We propose ontological blending as a new method for `creatively' combining ontologies. In contrast to other combination techniques that aim at integrating or assimilating cate...
Joana Hois, Oliver Kutz, Till Mossakowski, John A....
Abstract. Ontology based data access (OBDA) is concerned with providing access to typically very large data sources through a mediating conceptual layer that allows one to improve ...
Elena Botoeva, Diego Calvanese, Mariano Rodriguez-...