Deepmind technologies limited (20240320438). ACTION SELECTION BASED ON ENVIRONMENT OBSERVATIONS AND TEXTUAL INSTRUCTIONS simplified abstract
Contents
ACTION SELECTION BASED ON ENVIRONMENT OBSERVATIONS AND TEXTUAL INSTRUCTIONS
Organization Name
Inventor(s)
Karl Moritz Hermann of Berlin (DE)
Felix George Hill of London (GB)
ACTION SELECTION BASED ON ENVIRONMENT OBSERVATIONS AND TEXTUAL INSTRUCTIONS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240320438 titled 'ACTION SELECTION BASED ON ENVIRONMENT OBSERVATIONS AND TEXTUAL INSTRUCTIONS
The patent application describes methods, systems, and apparatus for selecting actions to be performed by an agent interacting with an environment.
- Language encoder model processes text strings in a natural language to generate text embeddings.
- Observation encoder neural network processes observations characterizing the environment's state to generate observation embeddings.
- A subsystem selects actions for the agent based on current text and observation embeddings.
Potential Applications: - Autonomous vehicles - Robotics - Natural language processing systems
Problems Solved: - Enhancing agent decision-making in complex environments - Improving interaction between agents and their surroundings
Benefits: - Increased efficiency in agent actions - Enhanced adaptability to changing environments
Commercial Applications: Title: "Enhancing Agent Decision-Making Technology for Autonomous Systems" This technology can be utilized in autonomous vehicles, robotics, and natural language processing systems to improve decision-making processes, leading to more efficient and adaptable systems.
Questions about the technology: 1. How does this technology improve agent decision-making in complex environments? 2. What are the key features that set this technology apart from existing systems?
Frequently Updated Research: Stay updated on advancements in natural language processing, neural networks, and autonomous systems to understand how this technology can evolve in the future.
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 interacting with an environment. in one aspect, a system includes a language encoder model that is configured to receive a text string in a particular natural language, and process the text string to generate a text embedding of the text string. the system includes an observation encoder neural network that is configured to receive an observation characterizing a state of the environment, and process the observation to generate an observation embedding of the observation. the system includes a subsystem that is configured to obtain a current text embedding of a current text string and a current observation embedding of a current observation. the subsystem is configured to select an action to be performed by the agent in response to the current observation.
