# LSTM-Based Anomalous Behavior Detection in Multi-Agent Reinforcement Learning

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/lstm-based-anomalous-behavior-detection-in-multi-agent-reinforcement-learning/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Cameron Lischke,Tongtong Liu,Joe McCalmon,Md Asifur Rahman,Talal Halabi,Sarra Alqahtani |
| Citations | 2 |
| DOI | 10.1109/csr54599.2022.9850343 |
| Fields | Computer Science |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W4292055417 |
| Type | conference-paper |
| Year | 2022 |

## Paper authors

- [Md Asifur Rahman](https://scholariq.org/researchers/md-asifur-rahman/)

## Paper primary topic

- [Network Security and Intrusion Detection](https://scholariq.org/topics/network-security-and-intrusion-detection/)

## Paper topics

- [Network Security and Intrusion Detection](https://scholariq.org/topics/network-security-and-intrusion-detection/)
- [Advanced Malware Detection Techniques](https://scholariq.org/topics/advanced-malware-detection-techniques/)
- [Adversarial Robustness in Machine Learning](https://scholariq.org/topics/adversarial-robustness-in-machine-learning/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.