Research Article
Formal Model and Analysis for the Random Event in the Intelligent Car with Stochastic Petri Nets and Z
Table 1
Advantages and disadvantages of three reinforcement learning algorithms.
| Category | Representative algorithm | Advantage | Disadvantage |
| Value learning | DQN | It can solve high-dimensional complex problems and is not easy to fall into local optimum | Overfitting, low sample utilization, instability, poor convergence | Policy learning | Monte Carlo method | High stability and strong convergence | Large variance, slow convergence, the easy local optimal solution | Value policy learning | Actor-critic | Small variance, fast training, and can solve continuous problems | Low learning efficiency, large deviation, and poor stability |
|
|