PRE2019 3 Group7: Difference between revisions
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1 Create a simulated environment where AI based on neural networks can roam. | 1 Create a simulated environment where AI based on neural networks can roam. | ||
2 Edit factors such as amount of food and maximum speed of the AI to see how this influences the AI. | 2 Edit factors such as amount of food and maximum speed of the AI to see how this influences the AI. | ||
3 Analyze the results of step 2, iterate and try to find interesting stuff. | 3 Analyze the results of step 2, iterate and try to find interesting stuff. | ||
4 Document everything interesting | 4 Document everything interesting | ||
Revision as of 19:22, 8 February 2020
Group Members
| Name | Study | Student ID |
|---|---|---|
| Daan Schalk | 0962457 | |
| Job Willems | 1003011 | |
| Jasper Dellaert | 1252454 | |
| Sanne van Wijk | 1018078 | |
| Wietske Blijjenberg | 1025111 |
Subject
Simulating populations using AI.
Objectives
een AI simulatie maken waarin je factoren kan aanpassen en dan kijken wat er met de populatie gebeurt? Analyseren hoe betrouwbaar zo'n tool is
Users
Biologists, ecologists, government organisations making wildlife plans, education
State-of-the-art
- Multi-agent Based Simulation: Where Are the Agents? https://link.springer.com/chapter/10.1007/3-540-36483-8_1
- VORTEX: a computer simulation model for population viability analysis
https://www.publish.csiro.au/WR/WR9930045
- A Generalized Computer Simulation Model for Fish Population Studies
https://afspubs.onlinelibrary.wiley.com/doi/abs/10.1577/1548-8659(1969)98[505:AGCSMF]2.0.CO;2
- Artificial Intelligence techniques: An introduction to their use for modelling environmental systems
https://www.sciencedirect.com/science/article/abs/pii/S0378475408000505
- An artificial intelligence modelling approach to simulating animal habitat interactions
- Application of Multi-agent Simulation in Animal Epidemic Emergency Management: Take an Example of AFS (Africa Fever Swine) Policy
http://www.dpi-proceedings.com/index.php/dtetr/article/view/31843
- A Study of AI Population Dynamics with Million-agent Reinforcement Learning (2018)
https://dl.acm.org/doi/10.5555/3237383.3238096
Approach
1 Create a simulated environment where AI based on neural networks can roam.
2 Edit factors such as amount of food and maximum speed of the AI to see how this influences the AI.
3 Analyze the results of step 2, iterate and try to find interesting stuff.
4 Document everything interesting