Towards Machine Mind Evolution
We introduce the principles of symbolization and conceptualization of perceived reality. We show them as processes that are applicable inside of a computer mind. We derive those processes from principles of a human mind.We present process of higher order regular abstraction and state automata acceptance as possible machine reality realization mechanism.We present the algorithm for evolution of machine mind language. Verification of this algorithm is presented in functional language Haskell. On the output, we have obtained fine-grained parallel nonredundant structure. It is in super-combinator form and represents elements of a machine mind language. Count of elements applications highly exceeds the count of elements themselves. Instead of accumulating acquired information, they are dissolved in the language of a mind. Vice versa, the information can be reconstructed from this language. We show that non-redundancy of a machine language is the decisive criterion for restructuring the machine mind language in each moment of communication. It is like that, so we can achieve more powerful and abstract communication between humans and computers or between computers themselves.(original abstract)
- M. Bacıkova, J. Poruban, and D. Lakatos, "Defining domain language of graphical user interfaces." in SLATE, 2013, pp. 187-202.
- J. Poruban, M. Bacikova, S. Chodarev, and M. Nosal, "Pragmatic modeldriven software development from the viewpoint of a programmer: Teaching experience," in Computer Science and Information Systems (FedCSIS), 2014 Federated Conference on. IEEE, 2014, pp. 1647- 1656.
- J. Poruban, M. Forgac, M. Sabo, and M. Behalek, "Annotation based parser generator," Computer Science and Information Systems, vol. 7, no. 2, pp. 291-307, 2010.
- J. Kollar and E. Pietrikova, "Genetic evolution of programs," Central European Journal of Computer Science, vol. 4, no. 3, pp. 160-170, 2014.
- F. Javed, M. Mernik, B. R. Bryant, and A. Sprague, "An unsupervised incremental learning algorithm for domain-specific language development," Applied Artificial Intelligence, vol. 22, no. 7-8, pp. 707-729, 2008.
- M. O'neill, C. Ryan, M. Keijzer, and M. Cattolico, "Crossover in grammatical evolution," Genetic programming and evolvable machines, vol. 4, no. 1, pp. 67-93, 2003.
- C. Renfrew, Prehistory: the making of the human mind. Random House Digital, Inc., 2009, vol. 30.
- P. Gardenfors, "Symbolic, conceptual and subconceptual representations," in Human and Machine Perception. Springer, 1997, pp. 255-270.
- M. Pater and D. E. Popescu, "Multi-level database mining using afopt data structure and adaptive support constrains." International Journal of Computers, Communications & Control, vol. 3, no. 3, 2008.
- N. Chomsky, Syntactic structures. Walter de Gruyter, 2002.
- J. Kollar, "Formal processing of informal meaning by abstract interpretation," Smart Digital Futures 2014, vol. 262, p. 122, 2014.
- R. Smith, C. Estan, S. Jha, and S. Kong, "Deflating the big bang: fast and scalable deep packet inspection with extended finite automata," in ACM SIGCOMM Computer Communication Review, vol. 38, no. 4. ACM, 2008, pp. 207-218.
- J. L. Peterson, Petri net theory and the modeling of systems. Prenticehall Englewood Cliffs (NJ), 1981, vol. 132.