Implications of resource limitations for a conscious machine

A machine with human-like consciousness would be an extremely complex system. Prior work has demonstrated that the way in which information handling resources are organized (the resource architecture) in an extremely complex learning system is constrained within some specific bounds if the available resources are limited, and that there is evidence that the human brain has been constrained in this way. An architectural concept is developed for a conscious machine that is within the architectural bounds imposed by resource limitations. This architectural concept includes a resource driven architecture, a description of how conscious phenomena would be supported by information processes within that architecture, and a description of actual implementations of the key information processes. Other approaches to designing a conscious machine are reviewed. The conclusion is reached that although they could be capable of supporting human consciousness-like phenomena, they do not take into account the architectural bounds imposed by resource limitations. Systems implemented using these approaches to learn a full range of cognitive features including human-like consciousness would therefore require more information handling resources, could have difficulty learning without severe interference with prior learning, and could require add-on subsystems to support some conscious phenomena that emerge naturally as consequences of a resource driven architecture.

[1]  L. Andrew Coward.  A Functional Architecture Approach to Neural Systems , 2000 .

[2]  Marian Stewart Bartlett,et al.  Face recognition by independent component analysis , 2002, IEEE Trans. Neural Networks.

[3]  L. Andrew Coward,et al.  Pattern Thinking , 1990 .

[4]  Ron Sun,et al.  Hierarchical approaches to understanding consciousness , 2007, Neural Networks.

[5]  Stan Franklin,et al.  IDA, a Conscious Artifact? , 2006 .

[6]  N. Block.  On a confusion about a function of consciousness , 1995, Behavioral and Brain Sciences.

[7]  P. Haikonen.  The Cognitive Approach to Conscious Machines , 2003 .

[8]  Ron Chrisley.  'Consciousness as depiction' [Review] Igor Aleksander (2005) The world in my mind, my mind in the world: key mechanisms of consciousness in people, animals and machines , 2006 .

[9]  Kenneth S. Pope,et al.  The Stream of Consciousness , 1978 .

[10]  Timo Honkela,et al.  Proceedings of the International and Interdisciplinary Conference on Adaptive Knowledge Representation and Reasoning (AKRR'05), Espoo, Finland, June 15-17, 2005 , 2005 .

[11]  James E. Smith,et al.  The architecture of virtual machines , 2005, Computer.

[12]  Ron Sun,et al.  Criteria for an effective theory of consciousness and some preliminary attempts , 2004, Consciousness and Cognition.

[13]  Tamás D. Gedeon,et al.  Application of the Recommendation Architecture to Telecommunications Network Management , 2001, Int. J. Neural Syst..

[14]  Michael N. Shadlen,et al.  Synchrony Unbound A Critical Evaluation of the Temporal Binding Hypothesis , 1999, Neuron.

[15]  Igor Aleksander.  Machine consciousness , 2005, Scholarpedia.

[16]  A. N. Bowers,et al.  Visual circuits of the avian telencephalon: evolutionary implications , 1999, Behavioural Brain Research.

[17]  A. Treisman.  Contextual Cues in Selective Listening , 1960 .

[18]  M. Shanahan.  A cognitive architecture that combines internal simulation with a global workspace , 2006, Consciousness and Cognition.

[19]  L. P. Chambers,et al.  Does Consciousness Exist , 1930 .

[20]  K. Szpunar,et al.  Episodic future thought and its relation to remembering: Evidence from ratings of subjective experience , 2008, Consciousness and Cognition.

[21]  L. A. Coward,et al.  Some Criteria for an Effective Scientific Theory of Consciousness and Examples of Preliminary Attempts at Such a Theory , 2003 .

[22]  Pentti O. A. Haikonen.  Robot Brains: Circuits and Systems for Conscious Machines , 2007 .

[23]  Murray Shanahan,et al.  A Simulated Global Neuronal Workspace with Stochastic Wiring , 2007, AAAI Fall Symposium: AI and Consciousness.

[24]  Amir Hussain,et al.  Brain Inspired Cognitive Systems 2008 , 2009 .

[25]  L. Andrew Coward.  Accounting for Episodic, Semantic and Procedural Memory in the Recommendation Architecture Cognitive Model , 2005 .

[26]  Alana T. Wong,et al.  Remembering the past and imagining the future: Common and distinct neural substrates during event construction and elaboration , 2007, Neuropsychologia.

[27]  Axel Cleeremans.  Computational correlates of consciousness. , 2005, Progress in brain research.

[28]  L. Andrew Coward.  A System Architecture Approach to the Brain: From Neurons to Consciousness , 2005 .

[29]  L. A. Coward,et al.  SIMULATION OF A PROPOSED BINDING MODEL , 2004 .

[30]  Anthony V. Robins,et al.  Catastrophic Forgetting, Rehearsal and Pseudorehearsal , 1995, Connect. Sci..

[31]  Fiona E. N. LeBeau,et al.  Microcircuits in action – from CPGs to neocortex , 2005, Trends in Neurosciences.

[32]  Tamás D. Gedeon,et al.  Managing Interference Between Prior and Later Learning , 2004, ICONIP.

[33]  James L. McClelland,et al.  Why there are complementary learning systems in the hippocampus and neocortex: insights from the successes and failures of connectionist models of learning and memory. , 1995, Psychological review.

[34]  R. French.  Catastrophic forgetting in connectionist networks , 1999, Trends in Cognitive Sciences.

[35]  L. Andrew Coward.  The recommendation architecture: lessons from large-scale electronic systems applied to cognition , 2001, Cognitive Systems Research.

[36]  D. Debanne,et al.  The role of dendritic filtering in associative long-term synaptic plasticity. , 1999, Learning & memory.

[37]  Christoph von der Malsburg,et al.  The Correlation Theory of Brain Function , 1994 .

[38]  Keiji Tanaka.  Columns for complex visual object features in the inferotemporal cortex: clustering of cells with similar but slightly different stimulus selectivities. , 2003, Cerebral cortex.

[39]  Christoph von der Malsburg,et al.  The What and Why of Binding The Modeler’s Perspective , 1999, Neuron.

[40]  Aaron Sloman,et al.  Virtual Machines and Consciousness , 2003 .

[41]  Bai-ling Zhang,et al.  Results of simulations of a system with the recommendation architecture , 1999, ICONIP'99. ANZIIS'99 & ANNES'99 & ACNN'99. 6th International Conference on Neural Information Processing. Proceedings (Cat. No.99EX378).

[42]  G. Hesslow.  Conscious thought as simulation of behaviour and perception , 2002, Trends in Cognitive Sciences.

[43]  G. Bi,et al.  Synaptic Modifications in Cultured Hippocampal Neurons: Dependence on Spike Timing, Synaptic Strength, and Postsynaptic Cell Type , 1998, The Journal of Neuroscience.

[44]  W. K. Simmons,et al.  A common neural substrate for perceiving and knowing about color , 2007, Neuropsychologia.