A solution for the Elevators Group Dispatch by Multiagent Reinforcement Learning

  • Jordão Memória Universidade Estadual do Ceará
  • José Maia Universidade Estadual do Ceará


In this work, a modeling and algorithm based on multiagent reinforcement learning is developed for the problem of elevator group dispatch. The main advantage is that, along with the function approximation, this multi-agent solution leads to reduction of the state space, allowing complex states to be addressed with a synthesizing evaluation function. Each elevator is considered an agent that have to decide about two actions: answer or ignore the new call. With some iterations, the agents learn the weights of an evaluation function which approximate the state-action value function. The performance of solution (average waiting time - AWT), shown varying the traffic pattern, flow of people, number of elevators and number of floors, is comparable to other current proposals reported in the literature.


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MEMÓRIA, Jordão; MAIA, José. A solution for the Elevators Group Dispatch by Multiagent Reinforcement Learning. In: ENCONTRO NACIONAL DE INTELIGÊNCIA ARTIFICIAL E COMPUTACIONAL (ENIAC), 16. , 2019, Salvador. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2019 . p. 646-657. ISSN 2763-9061. DOI: https://doi.org/10.5753/eniac.2019.9322.