Abstract
Unity3D is a game development environment that could be co-opted for agent-based machine learning research. We present a GUI-driven, and efficient Genetic Programming (GP) system for this purpose. Our system, ABL-Unity3D, addresses challenges entailed in co-opting Unity3D: making the simulator serve agent learning rather than humans playing a game, lowering fitness evaluation time to make learning computationally feasible, and interfacing GP with an AI Planner to support hybrid algorithms that could improve performance. We achieve this through development of a GUI using the Unity3D editor's programmable interface, and performance optimizations. These optimizations result in at least a 3x speed up. We describe ABL-Unity3D by explaining how to use it for an example experiment using GP and AI Planning.
| Original language | English |
|---|---|
| Title of host publication | GECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference |
| Publisher | Association for Computing Machinery, Inc |
| Pages | 2310-2313 |
| Number of pages | 4 |
| ISBN (Electronic) | 9781450392686 |
| DOIs | |
| State | Published - Jul 9 2022 |
| Externally published | Yes |
| Event | 2022 Genetic and Evolutionary Computation Conference, GECCO 2022 - Virtual, Online, United States Duration: Jul 9 2022 → Jul 13 2022 |
Publication series
| Name | GECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference |
|---|
Conference
| Conference | 2022 Genetic and Evolutionary Computation Conference, GECCO 2022 |
|---|---|
| Country/Territory | United States |
| City | Virtual, Online |
| Period | 07/9/22 → 07/13/22 |
Funding
This research was, in part, funded by the U.S. Government. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the U.S. Government.
Keywords
- AI planning
- GUI
- Unity3D
- genetic programming
- simulator