mlsanityData to 14 Oct 2026

Spiking Neural Network Predicting Sequence of the External Worlds States in Model-Based Reinforcement Learning

arXiv 2609.27459 ↗First posted 23 Sep 2026cs.NEcited by 0

On the map: Deep reinforcement learning methods → Spiking and neuromorphic RL

Abstract (arXiv)

This paper presents a spiking neural network (SNN) designed to predict the sequence of the external world states starting from the current world state. This SNN does not create the world dynamics model - instead it incorporates the SNN trained to predict the next world state and provides all mechanisms necessary to make the chain of predicted world states. These mechanisms are entirely spiking - they are implemented as spiking neuron ensembles. The present article describes this neuronal structure and tests its operation on a classic RL benchmark - ATARI ping-pong.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Spiking and neuromorphic RL, one of 15 directions in Deep reinforcement learning methods. Builds on 4 of its 19 references that are in the map. First posted on arXiv 23 Sep 2026.

Builds on

4 of 19 references.

Closest ancestors · 1

Same direction, newest first

  1. 2025Spiking World Model with Multi-Compartment Neurons for Model-based Reinforcement Learning2 Mar

Other references · 3

  1. 2019Surrogate Gradient Learning in Spiking Neural Networkscited by 626
  2. 2025Continual Learning with Columnar Spiking Neural Networkscited by 2
  3. 2022A Spiking Neural Network Learning Markov Chaincited by 1

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Not cited yet.

Similar, not cited

Close in wording, no citation either way

  1. 2024GRSN: Gated Recurrent Spiking Neurons for POMDPs and MARL
  2. 2024Fully Spiking Actor Network with Intra-layer Connections for Reinforcement Learning
  3. 2024CoLaNET -- A Spiking Neural Network with Columnar Layered Architecture for Classification
  4. 2025Energy-Efficient Deep Reinforcement Learning with Spiking Transformers
  5. 2025Adaptive Surrogate Gradients for Sequential Reinforcement Learning in Spiking Neural Networks
  6. 2025Spiking Decision Transformers: Local Plasticity, Phase-Coding, and Dendritic Routing for Low-Power Sequence Control
  7. 2023Learning Long Sequences in Spiking Neural Networks
  8. 2023SEENN: Towards Temporal Spiking Early-Exit Neural Networks