Technology of Complex Activity

Belov M, Novikov D (2018) Methodology of complex activity. Lenand, Moscow, 320 pp (in Russian)Google Scholar

Novikov D (2013) Theory of control in organizations. Nova Science Publishers, New York, 341 ppGoogle Scholar

Rebovich G, White B (2011) Enterprise systems engineering: advances in the theory and practice. CRC Press, Boca Raton, 459 ppGoogle Scholar

Novikov A, Novikov D (2007) Methodology. Sinteg, Moscow, 668 pp (in Russian)Google Scholar

Schwab K (2016) The fourth industrial revolution. World Economic Forum, Geneva, 172 ppGoogle Scholar

De Smet A, Lund S, Schaininger W (2016) Organizing for the future, McKinsey Q, Jan 2016. http://www.mckinsey.com/insights/organization/organizing-for-the-future

ISO/IEC/IEEE 15288:2015 systems and software engineering—system life cycle processesGoogle Scholar

Business Process Model and Notation (BPMN), v2.0.2. http://www.omg.org/spec/BPMN/2.0

Henriques D, Martins JG, Zuliani P, Platzer A, Clarke EM (2012) Statistical model checking for Markov decision processes. In: International Conference on Quantitative Evaluation of Systems (QEST), London, pp 84–93Google Scholar

Aichernig B, Schumi R (2017) Statistical model checking meets property-based testing. In: 2017 IEEE International Conference on Software Testing, Verification and Validation (ICST), Tokyo, pp 390–400Google Scholar

Alagoz H, German R (2017) A selection method for black box regression testing with a statistically defined quality level. In: 2017 IEEE International Conference on Software Testing, Verification and Validation (ICST), Tokyo, pp 114–125Google Scholar

Ali S, Yue T (2015) U-test: evolving, modelling and testing realistic uncertain behaviours of cyber-physical systems. In: 2015 IEEE 8th International Conference on Software Testing, Verification and Validation (ICST), Graz, pp 1–2Google Scholar

Bourque P, Fairley RE (eds) (2014) Guide to the software engineering body of knowledge, Version 3.0. IEEE Computer Society, 2014. www.swebok.org

Legay A, Delahaye B, Bensalem S (2010) Statistical model checking: an overview. In: Barringer H et al (eds) Runtime Verification. RV 2010. Lecture notes in computer science, vol 6418. Springer, Berlin, pp 122–135CrossRefGoogle Scholar

Patrick M, Donnelly R, Gilligan C (2017) A toolkit for testing stochastic simulations against statistical oracles. In: 2017 IEEE International Conference on Software Testing, Verification and Validation (ICST), Tokyo, pp 448–453Google Scholar

Yizhen C et al (2017) Effective online software anomaly detection. In: Proceedings of the 26th ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA 2017), Santa Barbara, pp 136–146Google Scholar

Orseau L, Lattimore T, Hutter M (2013) Universal knowledge-seeking agents for stochastic environments. In: Jain S, Munos R, Stephan F, Zeugmann T (eds) Algorithmic Learning Theory. ALT 2013. Lecture notes in computer science, vol 8139, Springer, Berlin, pp 158–172Google Scholar

Stocia G, Stack B (2017) Acquired knowledge as a stochastic process. Surv Math Appl 12:65–70MathSciNetGoogle Scholar

Wong A, Wang Y (2003) Pattern discovery: a data driven approach to decision support. IEEE Trans Syst Man Cybern 33(1):114–124CrossRefGoogle Scholar

Crawford J (1944) Learning curve, ship curve, ratios, related data. Lockheed Aircraft Corporation, pp 122–128Google Scholar

Henderson B (1984) The application and misapplication of the learning curve. J Bus Strategy 4:3–9CrossRefGoogle Scholar

Wright T (1936) Factors affecting the cost of airplanes. J Aeronaut Sci 3(4):122–128CrossRefGoogle Scholar

Chui D, Wong A (1986) Synthesizing knowledge: a cluster analysis approach using event covering. IEEE Trans Syst Man Cybern 16(2):251–259CrossRefGoogle Scholar

Leibowitz N, Baum B, Enden G, Karniel A (2010) The exponential learning equation as a function of successful trials results in sigmoid performance. J Math Psychol 54:338–340MathSciNetCrossRefGoogle Scholar

Thurstone L (1919) The learning curve equation. Psychol Monogr 26(3):1–51CrossRefGoogle Scholar

Thurstone L (1930) The learning function. J Gen Psychol 3:469–493CrossRefGoogle Scholar

Sutton R, Barto A (2016) Reinforcement learning: an introduction. MIT Press, Massachusetts, 455 ppGoogle Scholar

van der Linden WJ, Hambleton RH (1996) Handbook of modern item response theory, Springer, New York, 512 ppGoogle Scholar

Shiryaev A (1973) Statistical sequential analysis: optimal stopping rules. American Mathematical Society, New York, 174 ppGoogle Scholar

Mikami S, Kakazu Y (1993) Extended stochastic reinforcement learning for the acquisition of cooperative motion plans for dynamically constrained agents. In: Proceedings of IEEE Systems Man and Cybernetics Conference (SMC), Le Touquet, vol 4, pp 257–262Google Scholar

Novikov D (1998) Laws of iterative learning. Trapeznikov Institute of Control Sciences RAS, Moscow, 98 pp (in Russian)Google Scholar