I have a problem during the environmental modeling that I am developing. I highlighted the code below to highlight the problem. So, let's say I have 3 places of varying quality. The animal wants to move to a place of high quality (the higher the number, the higher the quality), but cannot distinguish qualities that differ less than or equal to 0.1 (this is part of a larger cycle, so this process will be repeated thousands of times).
For example, in this case (where the person starts at location # 2):
a<-matrix(c(1,2,3,.6,.9,.7),nrow=2,ncol=3,byrow=TRUE)
attributes(a)$dimnames<-list(c("Location","Quality"),c())
a
[,1] [,2] [,3]
Location 1.0 2.0 3.0
Quality 0.6 0.9 0.7
A person will clearly determine location No. 2 as the best and will remain there.
In this case (where the person starts at location # 2):
a<-matrix(c(1,2,3,.5,.7,.8),nrow=2,ncol=3,byrow=TRUE)
attributes(a)$dimnames<-list(c("Location","Quality"),c())
a
[,1] [,2] [,3]
Location 1.0 2.0 3.0
Quality 0.5 0.7 0.8
№ 2 № 3 ( 0,1, ), ( № 2 , ). , , №2 №3 , № 1 .
( , # 2)
a<-matrix(c(1,2,3,.9,.7,.6),nrow=2,ncol=3,byrow=TRUE)
attributes(a)$dimnames<-list(c("Location","Quality"),c())
a
[,1] [,2] [,3]
Location 1.0 2.0 3.0
Quality 0.9 0.7 0.6
2 1.
( , # 2)
a<-matrix(c(1,2,3,.8,.7,.6),nrow=2,ncol=3,byrow=TRUE)
attributes(a)$dimnames<-list(c("Location","Quality"),c())
a
[,1] [,2] [,3]
Location 1.0 2.0 3.0
Quality 0.8 0.7 0.6
№3 №1 № 2 # 1
, , , ( , ), ( , , ).