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JournalInternational Journal of Computer Applications
TitleProposing ELA: Environmental Learning Algorithm for Enhancing Humans and Epigenetic Robotics Skills
Index TermAlgorithms
AbstractRecently epigenetic robotics has been emerged as a new cognitive modeling approach in the field of artificial intelligence for modeling of autonomous mental development. The paper aims to develop new behavioral skills in the epigenetic robotics in different environment that would facilitate in enhancing the learning skills of humans utilizing machines. In an attempt to improve child mental development and growth, this revolutionary technology based upon artificial intelligence would be utilized for further development of machines that would behave like humans in a natural way. Utilizing the technique mentioned in the algorithm “ELA” (Environment Learning Algorithm), the humans will learn from machines and enhance their capabilities for better performance. The additional benefit for utilizing epigenetic robotics is to learn new skills autonomously through social interactions from different environments. The epigenetic robotics helps to remove the constraints on robotics that are already programmed pertaining to specifically task dependent.
KeywordsNatural intelligence, artificial intelligence, epigenetic robotics, skills, behavior, Robotics Social Interaction (RSI).
No. of Pages5
Author NamesInderpal Singh
  1. Shen Qiang, Zhou Changle, Jiang Min, Meng Qinggang, Shang Changing, November 2014. A Developmental approach to robotics pointing via human robot interaction ,New Trend of computational intelligence in HRI, ELSEVIER.
  2. Breazeal Cynthia, 2009. Role of expressive behavior for robots that learn from people, Philosophical Transactions of the royal society.
  3. Cheng Gordon & Atkeson Christopher, 2006. Coaching-An approach to efficiently & intuitively create humanoid robot behaviors, IEEE.
  4. Simmons Reid, Forlizzi Jodi and Gockley Rachel, 2007. Natural Person following behavior for social robots, ACM, Virginia, USA.
  5. [Stoytchev. 2009. Some basic principles of developmental robotics, IEEE Computational Intelligence Society.
  6. Shen Min Wei & Ranasinghe Nadeesha, 2008. Surprise based learning for developmental Robotics, ECSIS Symposium on Learning and adaptive behavior for robotics system, IEEE.
  7. Language Learning in children and robotics: - A Developmental Robotics Approach.
  8. Zeschel Arne.Saunders Joe & Dautenhahn Kersin, September 2010. Integration of action and language knowledge: A Roadmap for developmental robotics, IEEE Transaction autonomous mental developmental.
  9. Talbott, 2015. Learning to perceive: A Developmental robotics approach to vision and object interaction, PhD Thesis, California.
  10. Bogdan Raducance, Cognitive DR: An intrinsic Motivation system to support social interactions.
  11. Thelen Esther, Sur Mriganka & Stockman Ida, Autonomous Mental Development by robots and Animals, Access via science online site Pass.
  12. Abry Christian & Schwartz Luc Jean, 2012. A Developmental robotics system for visual scene perception and language Acquisition , International program for robot cognition planning document, PhD Thesis, France.
  13. Schlesinger Matthew & Cangelosi Angelo, Developmental Robotics: From babies to robots, Intelligent robotics and autonomous Agents, MIT Press.
  14. Konidaris. D George & Stout Andrew, Intrinsically Motivated Reinforcement Learning: - A Promising framework for developmental robot learning, Cite seer.
  15. Hollich.J.George, Holder’s Nathan & Prince G.Christopher, Ongoing emergence- A Core Concept in epigenetic robotics, proceeding of the 5th international workshop on epigenetic robot: Modeling cognitive development in robotic system.
  16. Bard Kim, An epigenetic approach aids the study of primate social cognition, proceeding of the 9th international conference on epigenetic robotics: Modeling cognitive development in robotics system, UK.
  17. Cangelosi Angelo and Belpeame Tone, December 2010. Epigenetic Robotics Architecture, IEEE Transactions on autonomous mental development, USA.
  18. Weng Juyang, 2004. Developmental robotics - Theory and experiments, Embodied intelligence laboratory-International journal of humanoid robotics, World Scientific publishing company.
  19. Philibert A.Robert, beach H.R Steven & Dogan V.Meeshanthini, Current and future Prospects for epigenetic biomarkers of substance use disorders, USA.
  20. Epigenetic Marks by foundations for a child’s future abilities, University of Southampton, 2015.
  21. Bell .J Anthony, 2013. Levels and Loops: The future of Artificial Intelligence, The royal Society, USA.

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