Reviewing different Neural Network Models for Multi-Agent games on Arm using Unity
September 12, 2023
During the Game Developer Conference (GDC) in March 2023, we showcased our multi-agent demo called Candy Clash, a mobile game containing 100 intelligent agents. In the demo, the agents are developed using Unity’s ML-Agents Toolkit which allows us to train them using reinforcement learning (RL). To find out more about the demo and its development, see our previous blog series. Previously, the agents had a simple Multi-Layer Perceptron (MLP) Neural Network (NN) model. This blog explores the impact of using other types of neural networks models on the gaming experience and performance.
To read the full article, click here
Related Semiconductor IP
- NPU IP Core for Mobile
- NPU IP Core for Edge
- Specialized Video Processing NPU IP
- HYPERBUS™ Memory Controller
- AV1 Video Encoder IP
Related Blogs
- Benefit of pruning and clustering a neural network for before deploying on Arm Ethos-U NPU
- Neural Network Model quantization on mobile
- Develop Software for the Cortex-M Security Extensions Using Arm DS and Arm GNU Toolchain
- Efficiently Packing Neural Network AI Model for the Edge
Latest Blogs
- Cadence Extends Support for Automotive Solutions on Arm Zena Compute Subsystems
- The Role of GPU in AI: Tech Impact & Imagination Technologies
- Time-of-Flight Decoding with Tensilica Vision DSPs - AI's Role in ToF Decoding
- Synopsys Expands Collaboration with Arm to Accelerate the Automotive Industry’s Transformation to Software-Defined Vehicles
- Deep Robotics and Arm Power the Future of Autonomous Mobility