This thesis discusses how an AI system having a TalaMind architecture and using the Tala language could support ‘higher-level mentalities’ of human-level intelligence, including natural language understanding, self-programming and higher-level learning, multi-level reasoning, curiosity, imagination, etc.
The approach involves developing an AI system using a language of thought based on the unconstrained syntax of a natural language; designing this system as a collection of concepts that can create and modify concepts, expressed in the language of thought, to behave intelligently in an environment; and using methods from cognitive linguistics such as mental spaces and conceptual blends for multiple levels of mental representation and computation.
The thesis endeavors to address all the major theoretical issues and objections that might be raised against its approach, or against the possibility of achieving human-level AI in principle. No insurmountable objections are identified, and arguments refuting several objections are presented.
The thesis describes the design of a prototype demonstration system, and discusses processing in the system that illustrates the potential of the research approach to achieve human-level AI.
The thesis does not claim to actually achieve human-level AI. It only presents a theoretical direction that may eventually reach this goal, and identifies areas for future AI research to further develop the approach. These include areas previously studied by others which were outside the scope of the thesis, such as ontology, common sense knowledge, spatial reasoning and visualization, etc.
Toward Human-Level Artificial Intelligence
Representation and Computation of Meaning in Natural Language
Philip C. Jackson, Jr.
Doctoral Thesis, Tilburg University, 2014
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