<abstract xmlns="http://www.w3.org/1999/xhtml"> Significant debate on fundamental issues remains in the subfields of cognitive science, including perception, memory, attention, action selection, learning, and others. Psychology, neuroscience, and artificial intelligence each contribute alternative and sometimes conflicting perspectives on the supervening problem of artificial general intelligence (AGI). Current efforts toward a broad-based, systems-level model of minds cannot await theoretical convergence in each of the relevant subfields. Such work therefore requires the formulation of tentative hypotheses, based on current knowledge, that serve to connect cognitive functions into a theoretical framework for the study of the mind. We term such hypotheses “conceptual commitments” and describe the hypotheses underlying one such model, the Learning Intelligent Distribution Agent (LIDA) Model. Our intention is to initiate a discussion among AGI researchers about which conceptual commitments are essential, or particularly useful, toward creating AGI agents.</abstract>

Fedex Institute of Technology 301, The University of Memphis, TN 38152, USA

6615 Fisher Ave. Falls Church, VA 22046, USA

Conceptual Commitments of the LIDA Model of Cognition

<abstract xmlns="http://www.w3.org/1999/xhtml"><bold>Editorial: Conceptual Commitments of AGI Systems</bold>Haris Dindo / James Marshall / Giovanni Pezzulo 23<bold>General Problems of Unified Theories of Cognition, and Another Conceptual Commitment of LIDA</bold>Benjamin Angerer / Stefan Schneider 26<bold>LIDA, Committed to Consciousness</bold>Antonio Chella 28<bold>The Radical Interactionism Conceptual Commitment</bold>Olivier L. Georgeon / David W. Aha 31<bold>Commitments of the Soar Cognitive Architecture</bold>John E. Laird 36	<bold>Conceptual Commitments of AGI Projects</bold>Pei Wang 39<bold>Will (dis)Embodied LIDA Agents be Socially Interactive?</bold>Travis J. Wiltshire / Emilio J. C. Lobato / Florian G. Jentsch / Stephen M. Fiore 42<bold>Author’s Response to Commentaries</bold>Steve Strain / Stan Franklin 48</abstract>

Conceptual Commitments of AGI Systems: Editorial, Commentaries, and Response

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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. 

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

Conceptual Commitments of AGI Systems, Editors:	Haris Dindo, James Marshall, and Giovanni Pezzulo

Volume 4 (2013): Issue 2 (December 2013)

Journal of Artificial General Intelligence

Volume 4 (2013): Issue 2 (December 2013)

Conceptual Commitments of AGI Systems, Editors: Haris Dindo, James Marshall, and Giovanni Pezzulo

Conceptual Commitments of the LIDA Model of Cognition

Conceptual Commitments of AGI Systems: Editorial, Commentaries, and Response

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