Neural network agents trained by declarative programming tutors - Publication - Bridge of Knowledge

Search

Neural network agents trained by declarative programming tutors

Abstract

This paper presents an experimental study on the development of a neural network-based agent, trained using data generated using declarative programming. The focus of the study is the application of various agents to solve the classic logic task – The Wumpus World. The paper evaluates the effectiveness of neural-based agents across different map configurations, offering a comparative analysis to underline the strengths and limitations of these approaches. We discuss the quantitative and qualitative aspects of these agents in scenarios that require generalization. For a concise comparison, we present the performance and resource utilization of different agents as follows: The Prolog- based agent showed a base task win rate of 61%, which dropped to 5% in a modified task setting, requiring 13KB of memory. The Q-Learning agent achieved a 2% win rate in the base task, with the modified task performance not applicable, and a memory requirement of 67KB. An agent based on a Convolutional Neural Network (CNN) recorded a 44% win rate on the base task and 32% on the modified task, consuming 134KB of memory. The Deep Q-Network (DQN) agent displayed a 56% win rate in the base task and 46% in the modified task, necessitating a substantial amount of memory, 284MB.

Citations

  • 0

    CrossRef

  • 0

    Web of Science

  • 0

    Scopus

Cite as

Full text

full text is not available in portal

Keywords

Details

Category:
Conference activity
Type:
publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
Language:
English
Publication year:
2024
Bibliographic description:
Dobrosolski J., Szymański J., Mora H., Draszawka K.: Neural network agents trained by declarative programming tutors// / : , 2024,
DOI:
Digital Object Identifier (open in new tab) 10.1109/cec60901.2024.10611953
Sources of funding:
  • Statutory activity/subsidy
Verified by:
Gdańsk University of Technology

seen 47 times

Recommended for you

Meta Tags