Why choose the probability of the first four phases of a neighbor?

[twodog0508]

Sorry, I would like to ask for some advice。
In each step, the AC algorithm is used to obtain the probability of the latest 5 phases of the neighbor. Why remove the probability of the last phase?
code：
def update_fingerprint(self, policy):
for node_name, pi in zip(self.node_names, policy):
self.nodes[node_name].fingerprint = np.array(pi)[:-1]

[JamesPsh]

@twodog0508
Hi,

I wanted to share my thoughts on why the probability of the last phase is removed in the code you mentioned.

In algorithms, the sum of all action probabilities is always 1.
Removing one probability doesn't affect this sum.
This increases the efficiency of the algorithm and reduces unnecessary calculations.

By removing the last probability, the overall distribution remains unchanged, allowing the algorithm to work smoothly.