Issue when m_u equals m_l

[tesslerc]

When updating the target distribution, if m_u == m_l == bj then the updated probability will be 0.

m_prob[action[i]][i][int(m_l)] += z_[optimal_action_idxs[i]][i][j] * (m_u - bj)
m_prob[action[i]][i][int(m_u)] += z_[optimal_action_idxs[i]][i][j] * (bj - m_l)

Easy fix is:

if m_u == m_l:
m_prob[action[i]][i][int(m_l)] += z_[optimal_action_idxs[i]][i][j]
else:
m_prob[action[i]][i][int(m_l)] += z_[optimal_action_idxs[i]][i][j] * (m_u - bj)
m_prob[action[i]][i][int(m_u)] += z_[optimal_action_idxs[i]][i][j] * (bj - m_l)

Same goes for when the target is a delta function (termination state):

.... else:
m_prob[action[i]][i][int(m_u)] += 1