preference or abstracted states. On the one hand, symbolic feedback can be easily generated by 
humans and effectively applied to the agent learning phase, such as a human's binary preference on an 
agent's actions or policies. On the other hand, different approaches for state abstractions will be 
considered to build up the knowledge base of safe or dangerous behaviours, such as spatial-temporal 
abstractions [4].  
 
Based on the symbolized preference and behaviour abstractions, there are several potential scenarios 
be explored:
informatics-phd-projects-2022-23