Analogical World Models- Perception, Action and Language Grounding through Analogical Prediction

Abstract

The PI, Dr. Karerina Fragkiadaki, propose an analogical framework for knowledge representation, perception and action from images and videos that encodes domain knowledge explicitly, in a collection of structured sensory experiences at different levels of spatial and temporal abstraction, in addition to implicitly, as network parameters. The proposed model retrieves memories and uses them to modulate perceptual inference to localize or generate analogous entities in the sensory stream, detect objects, parts, attributes, action-events, generate possible future and past action and event completions, evaluate counterfactuals, ground referentials, answer questions, and act in the environment. Each memory experience is encoded as a spatial-temporal graph of perceptual entities alongside a symbol(s), the symbols for roles, attributes, objects and actions.

Document Details

Document Type
DoD Grant Award
Publication Date
Feb 29, 2024
Source ID
FA95502310257

Entities

People

  • Katerina Fragkiadaki

Organizations

  • Air Force Office of Scientific Research
  • Carnegie Mellon University
  • United States Air Force

Tags

Readers

  • Artificial Intelligence
  • Computer Vision.

Technology Areas

  • AI & ML