Effects of Dynamic Goals on Agent Performance

Abstract

This research investigates how different categories of goals affect autonomous change detection in a dynamic environment. In order to accomplish this goal, a set of autonomous agents were developed to perform within an environment with multiple possible goals. The agents perform the environmental task while monitoring for goal changes. The experiment tests the agents over a range of goal changes to determine how detection performance is affected by the different categories of goals. Results show that detection is highly dependent on what goal is being switch to and from. The point similarity between goals is the most significant factor in evaluating the change detection time. An additional experiment improved upon the goal agent and demonstrated the importance of having the proper perception mechanics for feedback within the environment.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jun 14, 2018
Accession Number
AD1056649

Entities

People

  • Nathan R. Ball

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Biomedical
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Artificial Intelligence
  • Automation
  • Autonomous Agents
  • Autonomous Systems
  • Change Detection
  • Classification
  • Collision Avoidance
  • Computers
  • Data Mining
  • Department Of Defense
  • Detection
  • Engineering
  • Experimental Design
  • Human Machine Systems
  • Information Processing
  • Information Science
  • Motor Skills
  • Predictive Modeling
  • Probability
  • Situational Awareness
  • Test Methods
  • Trajectories
  • United States Government
  • Video Games

Readers

  • Sensor Fusion and Tracking Systems.
  • Systems Analysis and Design