Q-learning is one of the most popular reinforcement learning methods that allows an agent to learn the relationship between interval-valued state and action spaces, through a direct interaction with the environment. Fuzzy Q-learning is an extension to this algorithm to enable it to evolve Fuzzy Inference Systems (FIS) which range on continuous state and action spaces. In a FIS, the interaction ...

The Central American equine epizootic and epidemic of Venezuelan equine encephalitis (VEE) that began in June 1969 near the Guatemala-El Salvador border has been welldocumented (1-S). That outbreak spread southeast, reaching Guanacaste, Costa Rica, by 1970, and north, reaching southern Texas in 1971. The last known cases of equine infection by the exotic equine-virulent subtype I-AB strain of V...

We discuss the second quantization of scalar field theory on the q–deformed fuzzy sphere S2 q,N for q ∈ IR, using a path–integral approach. We find quantum field theories which are manifestly covariant under Uq(su(2)), have a smooth limit q → 1, and satisfy positivity and twisted bosonic symmetry properties. Using a Drinfeld twist, they are equivalent to ordinary but slightly “nonlocal” QFT’s o...

This paper addresses the problem of tuning the input and the output parameters of a fuzzy logic controller. The system learns autonomously without supervision or a priori training data. Two novel techniques are proposed. The first technique combines Q(λ)-learning with function approximation (fuzzy inference system) to tune the parameters of a fuzzy logic controller operating in continuous state...

We introduce a nonlinear variant of the voter model, the q-voter model, in which q neighbors (with possible repetition) are consulted for a voter to change opinion. If the q neighbors agree, the voter takes their opinion; if they do not have a unanimous opinion, still a voter can flip its state with probability epsilon . We solve the model on a fully connected network (i.e., in mean field) and ...

In crisp production inventory problem, let q, a, b, d, R and r be the quantity produced per cycle, the holding cost, production cost, production quantity per day, the total demand quantity and the demand quantity per day, respectively. We consider three fuzzification methods. Firstly, we fuzzify q, a, b, d, R and r to triangular fuzzy numbers. Secondly, we fuzzify d and r to triangular fuzzy nu...

The machinery of braided geometry introduced previously is used now to construct the ǫ ‘totally antisymmetric tensor’ on a general braided vector space determined by R-matrices. This includes natural q-Euclidean and q-Minkowski spaces. The formalism is completely covariant under the corresponding quantum group such as ̃ SOq(4) or ̃ SOq(1, 3). The Hodge ∗ operator and differentials are also cons...

Maji et al. introduced the concept of fuzzy soft sets as a generalization of the standard soft sets and presented an application of fuzzy soft sets in a decision making problem. The aim of this paper is to apply the concept of fuzzy soft sets to n-ary hypergroup theory. The concepts of (∈(γ), ∈(γ) ∨ q(δ))-fuzzy soft (invertible) n-ary subhypergroups over a commutative n-ary hypergroup are intro...

d Department of Mathematics and Statistics, University of Swat, Swat, Khyber Pakhtoonkhwa, Pakistan ABSTRACT The concept of interval-valued fuzzy set is one of the most important and useful generalisation of Zadeh's fuzzy sets which is successfully applied by engineers and scientists in the field of Robotics, Control Theory and Computer Engineering. In this paper, we introduce new and useful ge...

In a previous report, it was shown that nonviable Venezuelan equine encephalitis (VEE) vaccines prepared by exposure of virus suspensions produced in WI-38 cells to ionizing radiations were highly effective in protecting guinea pigs subjected to intraperitoneal (ip) challenge with VEE virus. To characterize further the efficacy of irradiated vaccines, guinea pigs were immunized with three lots ...