Contents
How are neural networks used in video games?
To observe how machine learning algorithms performed while playing video games, we used three models: NeuroEvolution of Augmenting Topologies (NEAT) from NEAT-Python, Proximal Policy Optimization (PPO) from OpenAI’s Baselines, and a curiosity-driven neural network from researchers from UC Berkeley, University of Edinburgh, and OpenAI.
Where can I find an introduction to neural networks?
The original article is published by Intel Game Dev on VentureBeat*: An introduction to neural networks with an application to games. Get more game dev news and related topics from Intel on VentureBeat.
What do you call a neural network on a computer?
This network, when simulated on a computer, is called an artificial neural network or neural net for short. Figure 1 shows a screen capture from a simple game that I put together to investigate the concept.
How does frame stacking work in a neural network?
By frame stacking, we can combine multiple frames into a single input for the model. Our model is actually choosing actions based on a series of frames that are “stacked together” instead of just a single frame. This allows the model to discern things like which way the character is moving or its velocity.
Can a neural network play Mortal Kombat 3?
For example, for Mortal Kombat 3 on the Sega Genesis console, a neural network would only be able to choose from the six buttons and the directional arrows on the original Sega Genesis controller. Each button is linked to a specific action (e.g. the “A” button corresponds to a Low Kick move).
How is neat a feed forward neural network?
NEAT is a feed-forward network describing individual networks using genomes. The algorithm evolves the network through generations using a fitness function. During training, the subsequent generations are produced through reproduction between high-scoring genomes along with some mutations.