<abstract xml:lang="en" xmlns="http://www.w3.org/1999/xhtml">Editors: Włodzisław Duch / Ah-Hwee Tan / Stan Franklin<bold>Autonomy for AGI</bold>Cristiano Castelfranchi 										31<bold>Are Disembodied Agents Really Autonomous?</bold>Antonio Chella											33<bold>The Perception-…-Action Cycle Cognitive Architecture and Autonomy: the View from the Brain</bold>Vassilis Cutsuridis										36<bold>Autonomy Requires Creativity and Meta-Learning</bold>Włodzisław Duch										39<bold>Meta Learning, Change of Internal Workings, and LIDA</bold>Ryan McCall / Stan Franklin									42<bold>An Appeal for Declaring Research Goals</bold>Brandon Rohrer											45<bold>The Development of Cognition as the Basis for Autonomy</bold>Frank van der Velde										47<bold>Autonomy and Intelligence</bold>Pei Wang											49<bold>Autonomy, Isolation, and Collective Intelligence</bold>Nikolaos Mavridis										51<bold>Response to Comments</bold>Kristinn R. Thórisson / Helgi Páll Helgasson							56
</abstract>

Cognitive architectures and autonomy: Commentary and Response

<abstract xml:lang="en" xmlns="http://www.w3.org/1999/xhtml">One of the original goals of artificial intelligence (AI) research was to create machines with very general cognitive capabilities and a relatively high level of autonomy. It has taken the field longer than many had expected to achieve even a fraction of this goal; the community has focused on building specific, targeted cognitive processes in isolation, and as of yet no system exists that integrates a broad range of capabilities or presents a general solution to autonomous acquisition of a large set of skills. Among the reasons for this are the highly limited machine learning and adaptation techniques available, and the inherent complexity of integrating numerous cognitive and learning capabilities in a coherent architecture. In this paper we review selected systems and architectures built expressly to address integrated skills. We highlight principles and features of these systems that seem promising for creating generally intelligent systems with some level of autonomy, and discuss them in the context of the development of future cognitive architectures. Autonomy is a key property for any system to be considered generally intelligent, in our view; we use this concept as an organizing principle for comparing the reviewed systems. Features that remain largely unaddressed in present research, but seem nevertheless necessary for such efforts to succeed, are also discussed.</abstract>

Center for Analysis & Design of Intelligent Agents, School of Computer Science Venus, 2nd fl. Reykjavik University Menntavegur 1, 101 Reykjavik, Iceland

Icelandic Institute for Intelligent Machines, 2. h. Uranus Menntavegur 1, 101 Reykjavik, Iceland

Cognitive Architectures and Autonomy: A Comparative Review

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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 3 (2012): Issue 2 (November 2012)

Cognitive architectures and autonomy: Commentary and Response

Cognitive Architectures and Autonomy: A Comparative Review

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