In this course, we will study human-like artificial agents, that is, autonomous intelligent agents situated in a virtual environment similar to the real world that act like humans. The course provides an overview of the types of such agents and their architectures, with an emphasis on action selection. The course also focuses on solving practical issues related to real-time and partially observable environments. The course is taught at MFF UK as NAIL133.
History: 2025, 2024, 2023, 2022, 2021, 2020, 2019, 2018, 2017, <=2016
This page contains information about lectures. If you’re looking for lab info, visit the Labs web page [TBD].
News
Follow the appropriate channel on Gamedev Discord!
https://discord.gg/c49DHBJ
Dates (SIS)
Lectures: Wednesday, 17:20-18:50, S5
Form: in real life (IRL), slides + some older video recordings will be made available
Start: exceptionally on Tuesday, March 3, 17:20 in S4, then on Wednesdays, 17:20-18:50, S5
Plan & Slides
| No. | Date | Topic | Lecturer | Form | Materials |
| 1. | 3.3.2026 (Tue) |
Introduction | Jakub Gemrot Petr Mácha |
Lecture IRL | |
| 2. | 11.3.2026 (Wed) |
Reactive Planning – Part I – If-then and alikes | Jakub Gemrot | Lecture IRL | |
| 3. | 18.3.2026 (Wed) |
Reactive Planning – Part II – Finite State Machines | Jakub Gemrot | Lecture IRL | PDF1, PDF2 |
| 4. | 25.3.2026 (Wed) |
Reactive Planning – Part III – Behavior Trees | Jakub Gemrot | Lecture IRL | |
| 5. | 1.4.2026 (Wed) |
Agent-based Modelling | Adam Streck | Lecture IRL | GDoc |
| 6. | 8.4.2026 (Wed) |
Agent-based Learning | Adam Streck | Lecture IRL | GDoc |
| 7. | 15.4.2025 (Wed) |
Steerings | František Mráz | Lecture IRL | |
| 8. | 22.4.2026 (Wed) |
Creating a Virtual Human(-oid) | Adam Streck | online | GDoc |
Exam & Grading
The exam will have two parts: 1
- a test-powered exam,
- a practical assignment, in which you will have to create a behavior for a NOTA robot squad or a group behavior for a squad in VBS4.
The final grade will be determined by the number of points you gather throughout the course.
These points are gained from:
- T = Test-powered exam in the form of a Moodle quiz (enroll in the Moodle course Human-like Artificial Agents with the enrollment key hlaa26), max. 40 points;
- L = Labs-final practical assignment (either in NOTA or VBS, your choice), max. 90 points;
- A = Advanced points gathered from homeworks, here you will take either points from NOTA or VBS (not both!), max. 40 points;
- Final Score = T + Max{LNOTA+ANOTA, LVBS4+AVBS4}
| Final Scoring | Final Grade |
| [0-90) | Fail |
| [90-105) | C |
| [105-120) | B |
| [120-170] | A |