18033289. AGENT MAP GENERATION simplified abstract (Hewlett-Packard Development Company, L.P.)

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AGENT MAP GENERATION

Organization Name

Hewlett-Packard Development Company, L.P.

Inventor(s)

SUNIL Kothari of PALO ALTO CA (US)

LEI Chen of PALO ALTO CA (US)

JACOB TYLER Wright of SAN DIEGO CA (US)

MARIA FABIOLA Leyva Mendivil of GUADALAJARA (MX)

JUN Zeng of PALO ALTO CA (US)

AGENT MAP GENERATION - A simplified explanation of the abstract

This abstract first appeared for US patent application 18033289 titled 'AGENT MAP GENERATION

Simplified Explanation

The abstract describes examples of apparatuses for agent map generation. These apparatuses include a memory to store a layer image and a processor coupled to the memory. The processor uses a machine learning model to generate an agent map based on the layer image.

  • The apparatus is used for agent map generation.
  • It includes a memory to store a layer image.
  • The apparatus also includes a processor that is coupled to the memory.
  • The processor utilizes a machine learning model to generate an agent map.
  • The agent map is based on the layer image stored in the memory.

Potential Applications

  • This technology can be used in video game development to generate maps for game agents.
  • It can be applied in autonomous vehicle navigation systems to create maps for the vehicle's decision-making.
  • The technology can be utilized in robotics to generate maps for robot agents.

Problems Solved

  • Traditional map generation methods may be time-consuming and require manual input.
  • This technology solves the problem of manual map generation by using a machine learning model.
  • It automates the process of generating agent maps, saving time and effort.

Benefits

  • The use of a machine learning model allows for efficient and accurate agent map generation.
  • The technology eliminates the need for manual map creation, reducing human error.
  • It can be easily integrated into existing systems and workflows.


Original Abstract Submitted

Examples of apparatuses for agent map generation are described. In some examples, an apparatus includes a memory to store a layer image. In some examples, the apparatus includes a processor coupled to the memory. In some examples, the processor is to generate, using a machine learning model, an agent map based on the layer image.

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