The article presents an approach toward the implementation of an Autonomous Intelligent Actor’s (AIA) [1] fuzzy control mechanism, when each step of it is based on dynamically defined scale. Such a scale is directed by fuzzy conditional inference rule. The approach, offered in the article, allows “soft landing” of AIA on a Target even in a case of “unfriendly” docking situation.
References
[1]
Tserkovny, A. (2022) Some Considerations about Fuzzy Logic Based Decision Making by Autonomous Intelligent Actor. Journal of Software Engineering and Applications, 15, 19-58. https://doi.org/10.4236/jsea.2022.152002
[2]
Tserkovny, A. (2017) A t-Norm Fuzzy Logic for Approximate Reasoning. Journal of Software Engineering and Applications, 10, 639-661. https://doi.org/10.4236/jsea.2017.107035
[3]
Genesereth, M. and Nilsson, N.J. (1989) Logical Foundations of Artificial Intelligence. Morgan Kaufmann Publishers, Los Altos. https://doi.org/10.1016/0004-3702(89)90073-8
[4]
Aliev, R.A. and Tserkovny, A. (1988) The Knowledge Representation in Intelligent Robots Based on Fuzzy Sets. Doklady Mathematics, 37, 541.
[5]
Aliev, R.A., Mamedova, G.A. and Tserkovny, A.E. (1991) Fuzzy Control Systems. Energoatomizdat, Moscow.
[6]
Fukami, S., Mizumoto, M. and Tanaka, K. (1980) Some Considerations of Fuzzy Conditional Inference. Fuzzy Sets and Systems, 4, 243-273. https://doi.org/10.1016/0165-0114(80)90014-7
[7]
Aliev, R.A. and Tserkovny, A. (2011) Systemic Approach to Fuzzy Logic Formalization for Approximate Reasoning. Information Sciences, 181, 1045-1059. https://doi.org/10.1016/j.ins.2010.11.021
