<abstract xmlns="http://www.w3.org/1999/xhtml">Sigma (Σ) is a cognitive architecture and system whose development is driven by a combination of four desiderata: <italic>grand unification</italic>, <italic>generic cognition</italic>, <italic>functional elegance</italic>, and <italic>sufficient efficiency</italic>. Work towards these desiderata is guided by the <italic>graphical architecture hypothesis</italic>, that key to progress on them is combining what has been learned from over three decades’ worth of separate work on <italic>cognitive architectures</italic> and <italic>graphical models</italic>. In this article, these four desiderata are motivated and explained, and then combined with the graphical architecture hypothesis to yield a rationale for the development of Sigma. The current state of the cognitive architecture is then introduced in detail, along with the graphical architecture that sits below it and implements it. Progress in extending Sigma beyond these architectures and towards a full cognitive system is then detailed in terms of both a systematic set of higher level <italic>cognitive idioms</italic> that have been developed and several <italic>virtual humans</italic> that are built from combinations of these idioms. Sigma as a whole is then analyzed in terms of how well the progress to date satisfies the desiderata. This article thus provides the first full motivation, presentation and analysis of Sigma, along with a diversity of more specific results that have been generated during its development.</abstract>

Institute for Creative Technologies and Department of Computer Science, 12015 Waterfront Dr. Playa Vista, CA 90094,

Institute for Creative Technologies, 12015 Waterfront Dr. Playa Vista, CA 90094,

The Sigma Cognitive Architecture and System: Towards Functionally Elegant Grand Unification

<abstract xmlns="http://www.w3.org/1999/xhtml">In the story <italic>Alice in Wonderland</italic>, Alice fell down a rabbit hole and suddenly found herself in a strange world called Wonderland. Alice gradually developed knowledge about Wonderland by observing, learning, and reasoning. In this paper we present the system A<sc>lice</sc> I<sc>n</sc> W<sc>onderland</sc> that operates analogously. As a theoretical basis of the system, we define several basic concepts of logic in a generalized setting, including the notions of domain, proof, consistency, soundness, completeness, decidability, and compositionality. We also prove some basic theorems about those generalized notions. Then we model Wonderland as an arbitrary symbolic domain and Alice as a cognitive architecture that learns autonomously by observing random streams of facts from Wonderland. Alice is able to reason by means of computations that use bounded cognitive resources. Moreover, Alice develops her belief set by continuously forming, testing, and revising hypotheses. The system can learn a wide class of symbolic domains and challenge average human problem solvers in such domains as propositional logic and elementary arithmetic.</abstract>

Department of Applied Information Technology, University of Gothenburg,

Department of Mathematical Sciences, Chalmers University of Technology,

Learning and Reasoning in Unknown Domains

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Journal of Artificial General Intelligence

 Journal of Artificial General Intelligence (JAGI) is a peer-reviewed open-access academic journal, owned by the Artificial General Intelligence Society (AGIS).  Artificial General Intelligence (AGI) is an emerging field aiming at the building of "thinking machines", that is, general-purpose systems with intelligence comparable to that of the human mind. While this was the original goal of Artificial Intelligence (AI), the mainstream of AI research has turned toward domain-dependent and problem-specific solutions; therefore it has become necessary to use a new name to indicate research that still pursues the "Grand AI Dream". Similar labels for this kind of research include "Strong AI", "Human-level AI", etc.  The problems involved in creating general-purpose intelligent systems are very different from those involved in creating special-purpose systems. Therefore, this journal is different from conventional AI journals in its stress on the long-term potential of research towards the ultimate goal of AGI, rather than immediate applications. Articles focused on details of AGI systems are welcome, if they clearly indicate the relation between the special topics considered and intelligence as a whole, by addressing the generality, extensibility, and scalability of the techniques proposed or discussed.  Since AGI research is still in its early stage, the journal strongly encourages novel approaches coming from various theoretical and technical traditions, including (but not limited to) symbolic, connectionist, statistical, evolutionary, robotic and information-theoretic, as well as integrative and hybrid approaches.  Rejection Rate  &gt;30%   Archiving  Sciendo archives the contents of this journal in Portico - digital long-term preservation service of scholarly books, journals and collections.  Plagiarism Policy  The editorial board is participating in a growing community of Similarity Check System's users in order to ensure that the content published is original and trustworthy. Similarity Check is a medium that allows for comprehensive manuscripts screening, aimed to eliminate plagiarism and provide a high standard and quality peer-review process. 

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Volume 7 (2016): Issue 1 (December 2016)

The Sigma Cognitive Architecture and System: Towards Functionally Elegant Grand Unification

Learning and Reasoning in Unknown Domains

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