# Is the bias supposed to be updated in the perceptron learning algorithm?

I am using the following perceptron formula $$\text{step}\left(\sum(w_ix_i)-\theta \right)$$.

Is $$\theta$$ supposed to be updated in a perceptron, like the weights $$w_i$$? If so, what is the formula for this?

I'm trying to make the perceptron learn AND and OR, but without updating $$\theta$$, I don't feel like it's possible to learn the case where both inputs are $$0$$. They will, of course, be independent of the weights, and therefore the output will be $$\text{step}(-\theta)$$, meaning $$\theta$$ (which has a random value) alone will determine the output.

Treat $$\theta$$ as a normal weight, associated with an input that always equals $$-1$$.