Cannot construct localized free energy algorithm. about forneylab.jl HOT 1 CLOSED

using ForneyLab

n_samples = 100
A = [1 1; 0 1] # Transtiion matrix
u = [0.5, 1] # Control vector
c = zeros(2); c[1] = 1 # unit vector (observation vector)
x = [A*[x_t, 1] for x_t in 1:n_samples] # real state
y = [c'x[t] + sqrt(100)*randn() for t in 1:n_samples] # noisy observations of postition

# Graph definition
g = FactorGraph()

@RV x_t_min ~ GaussianMeanVariance(placeholder(:m_x_t_min, dims=(2,)), 
                                   placeholder(:v_x_t_min, dims=(2, 2)))

@RV x_t = A*x_t_min
c = zeros(2); c[1] = 1;
@RV y_t ~ GaussianMeanPrecision(dot(c, x_t), 0.01)

placeholder(y_t, :y_t)

ForneyLab.draw(g)

# Specify recognition factorization
q = RecognitionFactorization(x_t, ids=[:X_t])
# Construct free energy algorithm
algoF = freeEnergyAlgorithm()

println(algoF)