Deepmind technologies limited (20240281654). AUTOREGRESSIVELY GENERATING SEQUENCES OF DATA ELEMENTS DEFINING ACTIONS TO BE PERFORMED BY AN AGENT simplified abstract

AUTOREGRESSIVELY GENERATING SEQUENCES OF DATA ELEMENTS DEFINING ACTIONS TO BE PERFORMED BY AN AGENT

Organization Name

deepmind technologies limited

Inventor(s)

Scott Ellison Reed of Atlanta GA (US)

Konrad Zolna of London (GB)

Emilio Parisotto of London (GB)

Tom Erez of London (GB)

Alexander Novikov of London (GB)

Jack William Rae of London (GB)

Misha Man Ray Denil of London (GB)

Joao Ferdinando Gomes De Freitas of London (GB)

Oriol Vinyals of London (GB)

Sergio Gomez of London (GB)

Ashley Deloris Edwards of London (GB)

Jacob Bruce of London (GB)

Gabriel Barth-maron of London (GB)

AUTOREGRESSIVELY GENERATING SEQUENCES OF DATA ELEMENTS DEFINING ACTIONS TO BE PERFORMED BY AN AGENT - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240281654 titled 'AUTOREGRESSIVELY GENERATING SEQUENCES OF DATA ELEMENTS DEFINING ACTIONS TO BE PERFORMED BY AN AGENT

The patent application describes methods, systems, and apparatus for selecting actions for an agent to interact with an environment using an action selection neural network.

• Generating a current representation of the state of a task being performed by the agent in the environment at each time step.
• Autoregressively generating a sequence of data elements representing a current action to be performed by the agent at the current time step.
• Causing the agent to perform the current action at the current time step after generating the sequence of data elements.

Potential Applications: - Autonomous vehicles - Robotics - Gaming industry

Problems Solved: - Efficient action selection for agents in dynamic environments - Improved decision-making processes for AI systems

Benefits: - Enhanced performance of agents in various tasks - Increased efficiency in interacting with complex environments

Commercial Applications: Title: "Enhanced Action Selection Technology for Autonomous Systems" This technology can be utilized in autonomous vehicles, robotic systems, and gaming applications to improve decision-making processes and enhance overall performance.

Questions about Action Selection Neural Network Technology: 1. How does this technology improve the efficiency of agents in dynamic environments? 2. What are the key advantages of using an action selection neural network in autonomous systems?

Frequently Updated Research: Stay updated on the latest advancements in neural network technology for action selection to ensure optimal performance in various applications.

Original Abstract Submitted

methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for selecting actions to be performed by an agent to interact with an environment using an action selection neural network. in one aspect, a method comprises, at each time step in a sequence of time steps: generating a current representation of a state of a task being performed by the agent in the environment as of the current time step as a sequence of data elements; autoregressively generating a sequence of data elements representing a current action to be performed by the agent at the current time step; and after autoregressively generating the sequence of data elements representing the current action, causing the agent to perform the current action at the current time step.