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Advanced AI in GamesLaajuus (5 cr)

Code: LTD7015

Credits

5 op

Teaching language

  • Finnish

Responsible person

  • Seppo Nevalainen

Objective

- You can utilize visualization and debugging strategies and tools for game AI.
- You understand the basic principles of utility-calculation based game AI reasoning and know hot to apply them in a game implementation.
- You can utilize perception and environment data as a part of game AI.
- You can design an AI architecture for a game through combination of different AI components.

Content

During the course we will familiarize ourselves with different visualization and debugging strategies and tools for game AI, utilization of perception and environment data, advanced pathfinding techniques, and utility-based AI reasoning. These techniques will be implemented also in practice as a part of a game project.

Enrollment

01.04.2024 - 30.04.2024

Timing

26.08.2024 - 20.10.2024

Number of ECTS credits allocated

5 op

Mode of delivery

Contact teaching

Campus

Wärtsilä Campus Karjalankatu 3

Teaching languages
  • Finnish
Seats

10 - 85

Degree programmes
  • Degree Programme in Business Information Technology
Teachers
  • Seppo Nevalainen
Teacher in charge

Seppo Nevalainen

Groups
  • DTNS21
    Information Technology (BBA), Full-time Studies, Fall, 2021

Objective

- You can utilize visualization and debugging strategies and tools for game AI.
- You understand the basic principles of utility-calculation based game AI reasoning and know hot to apply them in a game implementation.
- You can utilize perception and environment data as a part of game AI.
- You can design an AI architecture for a game through combination of different AI components.

Content

During the course we will familiarize ourselves with different visualization and debugging strategies and tools for game AI, utilization of perception and environment data, advanced pathfinding techniques, and utility-based AI reasoning. These techniques will be implemented also in practice as a part of a game project.

Evaluation scale

H-5

Enrollment

01.04.2023 - 15.04.2023

Timing

28.08.2023 - 22.10.2023

Number of ECTS credits allocated

5 op

Virtual portion

5 op

Mode of delivery

Distance learning

Campus

Wärtsilä Campus Karjalankatu 3

Teaching languages
  • Finnish
Seats

10 - 50

Degree programmes
  • Degree Programme in Business Information Technology
Teachers
  • Seppo Nevalainen
Teacher in charge

Seppo Nevalainen

Groups
  • LTDNS20
    Information Technology (BBA), Full-time Studies, Fall, 2020

Objective

- You can utilize visualization and debugging strategies and tools for game AI.
- You understand the basic principles of utility-calculation based game AI reasoning and know hot to apply them in a game implementation.
- You can utilize perception and environment data as a part of game AI.
- You can design an AI architecture for a game through combination of different AI components.

Content

During the course we will familiarize ourselves with different visualization and debugging strategies and tools for game AI, utilization of perception and environment data, advanced pathfinding techniques, and utility-based AI reasoning. These techniques will be implemented also in practice as a part of a game project.

Evaluation scale

H-5

Enrollment

01.04.2022 - 30.04.2022

Timing

29.08.2022 - 23.10.2022

Number of ECTS credits allocated

5 op

Mode of delivery

Contact teaching

Campus

Wärtsilä Campus Karjalankatu 3

Teaching languages
  • Finnish
Seats

20 - 60

Degree programmes
  • Degree Programme in Business Information Technology
Teachers
  • Seppo Nevalainen
Teacher in charge

Seppo Nevalainen

Groups
  • LTDNS19
    Information Technology (BBA), Full-time Studies, Fall, 2019

Objective

- You can utilize visualization and debugging strategies and tools for game AI.
- You understand the basic principles of utility-calculation based game AI reasoning and know hot to apply them in a game implementation.
- You can utilize perception and environment data as a part of game AI.
- You can design an AI architecture for a game through combination of different AI components.

Content

During the course we will familiarize ourselves with different visualization and debugging strategies and tools for game AI, utilization of perception and environment data, advanced pathfinding techniques, and utility-based AI reasoning. These techniques will be implemented also in practice as a part of a game project.

Evaluation scale

H-5