Accession Number:

ADA482256

Title:

Cognitive Models for Learning to Control Dynamic Systems

Descriptive Note:

Final rept. 30 Sep 2007-30 May 2008

Corporate Author:

COMPUTELLIGENCE LLC INDIANAPOLIS IN

Report Date:

2008-05-30

Pagination or Media Count:

79.0

Abstract:

Report developed under STTR contract for topic Cognitive models for learning to control dynamic systems demonstrated a swarm intelligence learning algorithm and its application in unmanned aerial vehicle UAV mission planning. A new UAV assignment model was developed that reduces the dimension of the solution space and is easily adapted by computational intelligence algorithms. A version of particle swarm optimization PSO was applied to accomplish the mission optimization. Numerical experimental results illustrate that it efficiently achieves the optima and demonstrates the effectiveness of combining the model and PSO to solve complex UAV assignment problems. The time to complete mission plans for operationally realistic scenarios is reduced by 3-4 orders of magnitude compared with the mixed-integer linear programming approach being used by AFRL at WPAFB. A computer game was also developed to investigate how humans interact with swarm intelligence. The game is based on an NK landscape. It is concluded that the combination of a human-swarm team may have advantages in certain environments, such as dynamic decision making tasks.

Subject Categories:

  • Numerical Mathematics
  • Operations Research
  • Computer Programming and Software
  • Pilotless Aircraft

Distribution Statement:

APPROVED FOR PUBLIC RELEASE