• Corpus ID: 17722510

Multi-Objective Deep Q-Learning with Subsumption Architecture

@article{Tajmajer2017MultiObjectiveDQ,
  title={Multi-Objective Deep Q-Learning with Subsumption Architecture},
  author={Tomasz Tajmajer},
  journal={ArXiv},
  year={2017},
  volume={abs/1704.06676}
}
  • T. Tajmajer
  • Published 21 April 2017
  • Computer Science
  • ArXiv
In this work we present a method for using Deep Q-Networks (DQNs) in multi-objective tasks. Deep Q-Networks provide remarkable performance in single objective tasks learning from high-level visual perception. However, in many scenarios (e.g in robotics), the agent needs to pursue multiple objectives simultaneously. We propose an architecture in which separate DQNs are used to control the agent's behaviour with respect to particular objectives. In this architecture we use signal suppression… 

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