Different useful approaches of implementing real-time AI? I identify myself as a human agent. It is time to think about oncoming senior research and due to small experience in gamedev(as well as in AI field), some questions are raised. What are the most suitable approaches to implement real-time simple AI agent in an action game? I've heard something about cognitive architecture like ACT-R.

By design, entity's AI can have several mutually exclusive states. 


This is an existing AI of game, which has states, events and schedules. However, the code is complicated and not flexible. Also, it does not use any cognitive architecture, which I consider as a drawback.
https://www.youtube.com/watch?v=9jO-P3kXlCI

Please, using your experience suggest any modern techniques, which can copy such behaviour as in image or video.

Thank you for your perception.
About 15 years ago, John Laird's group at Michigan used the Soar rule-based architecture to play several FPS games effectively (Quake II, Descent III):

http://ai.eecs.umich.edu/people/laird/games_research.html

Here's Laird's overview article from 'Computer':

https://www.researchgate.net/profile/John_Laird/publication/2955463_Laird_JE_Using_a_computer_game_to_develop_advanced_AI_Computer_34_70-75/links/54d0f59a0cf20323c21a1bd7/Laird-JE-Using-a-computer-game-to-develop-advanced-AI-Computer-34-70-75.pdf