Regulating the growth of complexity in developmental systems

Details Regulating the growth of complexity in developmental systems Regulating the growth of complexity in developmental systems

2004-07-07

2008-10-21

Hirl, Joseph P (Department: 2129)

Data processing: artificial intelligence

Machine learning

C706S014000, C706S015000

Reexamination Certificate

active

07440927

ABSTRACT:
Developmental systems (1/11) are provided with an autotelic mechanism for driving their development. An autotelic component (1) in the system uses a mapping mechanism (2) to produce an output based on a set of inputs. The mapping mechanism (2) implements a mapping that is dependent upon a state associated therewith. The content of the state is changed by a learning/repair module (3) based on interactions between the system and the environment, and so reflects knowledge gained by this component as a result of its experience. The autotelic component (1) monitors its own performance with reference to the level of a set of one or more challenge parameters whose levels quantify the complexity of different parameters relating to the autotelic component (1). The state associated with the mapping mechanism2is altered depending upon the component's performance as evaluated during the monitoring. A controller (5) controls the levels of the challenge parameters.

REFERENCES:
patent: 6516350 (2003-02-01), Lumelsky et al.
Kishan Mehrotra et al, Elements of Artificial Neural Networks, 1997, MIT.
Humberto E. Garcia, Reconfigurable Control of Power Plants Using Learning Automata, Jan. 1991, IEEE, 0272-1708/91/0100-0085, 85-92□□.
“Environmental complexity control for vision-based learning mobile robot” by Uchibe et al., from the Proceedings of the 1998 IEEE International Conference on Robotics and Automation (Leuven, Belgium, May 16-20, 1998), published by IEEE, New York, NY, USA, 1998, pp. 1865-1870.
“On the Interplay between morphological, neural and environmental dynamics: A robotic case study” by M. Lungarella and L. Berthouze, Adaptive Behaviour (on-line), vol. 1, No. 3-4, Jul. 1, 2002 retrieved from URL http://staff.aist.go.jp/luc.berthouze/papers/2003/ab03.pdf.
“Learning and development in neural networks: the importance of starting small” by J. Elman in “Cognition”, vol. 48, No. 1, (Jul. 1, 1993), pp. 71-99.
“Developing Haptic and Visual Perceptual Categories for Reaching and Grasping with a Humanoid Robot” by Jefferson A. Coelho et al., from “Robotics and Autonomous Systems”, soecial issue on humanoid robots, vol. 37, No. 2-3, pp. 195-215, 2001.
“Emergent Adaptive Lexicons” by L. Steels, in the Proceedings of the 4thInternational Conference on Simulation of Adaptive Behavior, “From Animals to Animats”, ed. P. Maes, The MIT Press, Cambridge Ma., 1996.
“Autonomous mental development by robots and animals” by J. Weng, J. McClelland, A. Pentland, O. Sporns, I. Stockman, M. Sur, & E. Thelen, in Science, 291, 599-600, 2001.
“Structures, inner values, hierarchies and stages: Essentials for developmental robot architectures” by A. Kulakov & G. Stojanov, in the Proceedings of the Second International Workshop on Epigenetic Robotics: Modeling Cognitive Development in Robotic Systems, ed. C.G. Prince et al., Lund University Cognitive Studies, Lund, Sweden (2002), vol. 94, pp. 63-69.
“Optimization by Simulated Annealing” by S. Kirkpatrick, C.D. Gerlatt Jr., and M.P. Vecchi, in “Science” 220, 671-680, (1983).
“Simulated annealing: Practice versus theroy” by L. Ingber in “Mathematical and Computer Modelling”, 18, 11, 29-57, (1993).
“Shared grounding of event descriptions by autonomous robots” by L. Steels and J-C Baillie, Robotics and Autonomous Systems, 43 (2003), pp. 163-173
“A constructivist model of infant cognition” by L. Cohen et al., in Cognitive Development, 17(2002) 1323-1343, (2002).
Chapter 1 of “Rethinking Innateness: A connectionist perspective on development” by J. L. Elman et al., MIT Press, Cambridge, Ma., USA (1996).
“Specialization of Neural Mechanisms Underlying Face Recognition in Human Infants” by Michelle de Haan, Oliver Pascalis, and Mark H. Johnson,Journal of Cognitive Neuroscience. 2002;14:199-209.
“Cortical specialization for higher cognitive functions: Beyond the maturational model” by M.H. Johnson, Brain and Cognition, 42, 124-127, (1996).
A brief history of connectionism by D. Medler. Neural Computing Surveys, vol. 1, p. 18-72).
“Neural Networks for Pattern Recognition” by C.M. Bischop, Oxford University Press, Oxford, UK, 1995.
“Development as a dynamic system”. By Thelen and L. Smith, vol. 7, 8, p. 343-348, 2003.
“A dynamic systems approach to the development of cognition and action” by B. Thelen and L. Smith, MIT Press, Cambridge Ma., 1996.
“Flow—A theory of optimal experience: History and Critical Evaluation”. By Walter John Carl, Theories of Communication, Rochester Institute of Technology, NY, USA, 1994 but not formally published—available on the Internet since an unknown date—see http://www.atsweb.neu.edu/w.carl/PDFS/flowpaper.pdf.
“Optimal Experience: Psychological Studies of Flow in Consciousness” ed. M. Csikszentmihalyi and I. Selega, Cambridge University Press, Cambridge, 2001, and “Beyond Boredom and Anxiety: Experiencing Flow in Work and Play” by M. Csikszentmihalyi, Cambridge University Press, Cambridge, 1978.

Affiliated with

Also associated with

Rating

Regulating the growth of complexity in developmental systems does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Regulating the growth of complexity in developmental systems, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Regulating the growth of complexity in developmental systems will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFUS-PAI-O-3987909