Script is the structured knowledge representation of prototypical real-life event sequences. Learning the commonsense knowledge inside the script can be helpful for machines in understanding natural language and drawing commonsensible inferences. Script learning is an interesting and promising research direction, in which a trained script learning system can process narrative texts to capture script knowledge and draw inferences. However, there are currently no survey articles on script learning, so we are providing this comprehensive survey to deeply investigate the standard framework and the major research topics on script learning. This research field contains three main topics: event representations, script learning models, and evaluation approaches. For each topic, we systematically summarize and categorize the existing script learning systems, and carefully analyze and compare the advantages and disadvantages of the representative systems. We also discuss the current state of the research and possible future directions.