Analysis of Generalized Artificial Intelligence Potential Through Reinforcement and Deep Reinforcement Learning Approaches
Abstract
Artificial Intelligence is the next competitive domain; the first nation to develop human level artificial intelligence will have an impact similar to the development of the atomic bomb. To maintain the security of the United States and her people, the Department of Defense has funded research into the development of artificial intelligence and its applications. This research uses reinforcement learning and deep reinforcement learning methods as proxies for current and future artificial intelligence agents and to assess potential issues in development. Agent performance were compared across two games and one excursion: Cargo Loading, Tower of Hanoi, and Knapsack Problem, respectively. Deep reinforcement learning agents were observed to handle a wider range of problems, but behave inferior to specialized reinforcement learning algorithms.
Document Details
- Document Type
- Technical Report
- Publication Date
- Mar 26, 2022
- Accession Number
- AD1173050
Entities
People
- Jonathan J Turner
Organizations
- Air Force Institute of Technology