PRE2019 3 Group7: Difference between revisions
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=Milestones= | =Milestones= | ||
=Deliverables= | =Deliverables= | ||
* An AI simulation tool | |||
* This wiki page, which contains our process, research and the results of our analysis. | |||
* A presentation | |||
Revision as of 19:29, 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
- Construct an AI simulation with which we can evaluate the likelihood of adverse ecological effects on populations occurring as a result of exposure to physical or chemical stressors
- Analysing the reliability of such a simulation by comparing the results to scenarios which have happened in the past.
- Analysing the possibilities and shortcomings of such a simulation.
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
Planning
Milestones
Deliverables
- An AI simulation tool
- This wiki page, which contains our process, research and the results of our analysis.
- A presentation