<abstract xmlns="http://www.w3.org/1999/xhtml"> In recent years broad community of researchers has emerged, focusing on the original ambitious goals of the AI field - the creation and study of software or hardware systems with general intelligence comparable to, and ultimately perhaps greater than, that of human beings. This paper surveys this diverse community and its progress. Approaches to defining the concept of Artificial General Intelligence (AGI) are reviewed including mathematical formalisms, engineering, and biology inspired perspectives. The spectrum of designs for AGI systems includes systems with symbolic, emergentist, hybrid and universalist characteristics. Metrics for general intelligence are evaluated, with a conclusion that, although metrics for assessing the achievement of human-level AGI may be relatively straightforward (e.g. the Turing Test, or a robot that can graduate from elementary school or university), metrics for assessing partial progress remain more controversial and problematic.</abstract>

Artificial General Intelligence: Concept, State of the Art, and Future Prospects

<abstract xmlns="http://www.w3.org/1999/xhtml"> An agent achieves its goals by interacting with its environment, cyclically choosing and executing suitable actions. An action execution process is a reasonable and critical part of an entire cognitive architecture, because the process of generating executable motor commands is not only driven by low-level environmental information, but is also initiated and affected by the agent’s high-level mental processes. This review focuses on cognitive models of action, or more specifically, of the action execution process, as implemented in a set of popular cognitive architectures. We examine the representations and procedures inside the action execution process, as well as the cooperation between action execution and other high-level cognitive modules. We finally conclude with some general observations regarding the nature of action execution.</abstract>

The Action Execution Process Implemented in Different Cognitive Architectures: A Review

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Volume 4 (2013): Issue 3 (December 2013) Brain Emulation and Connectomics: a Convergence of Neuroscience and Artificial General Intelligence, Editors: Randal Koene and Diana Deca

Volume 4 (2013): Issue 2 (December 2013) Conceptual Commitments of AGI Systems, Editors:	Haris Dindo, James Marshall, and Giovanni Pezzulo

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Volume 3 (2012): Issue 3 (December 2012) Self-Programming and Constructivist Methodologies for AGI,
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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. 

Journal of Artificial General Intelligence

Volume 5 (2014): Issue 1 (December 2014)

Artificial General Intelligence: Concept, State of the Art, and Future Prospects

The Action Execution Process Implemented in Different Cognitive Architectures: A Review

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