Integration of Deep Reinforcement Learning and Agent-based Simulation to Explore Strategies Counteracting Information Disorder
2026-04-16T08:52:22Z•396865b6b7e3ab77ba05bd53ddb0893af9437ee961ae5e79bf82088b6853a89c
API-keysEthereum-addressesJWTSSH-bruteforceagent-based-modelingagreement-driftcitation-farmingcredential-leakcritical-mass-collapsedeep-reinforcement-learninggraph-algorithmsinfluence-spreadinformation-disordermisinformation-mitigationmodel-competitionoffensive-securityopen-source-llm-ecosystemsplatform-securitypopularity-biasrecommendation-systemsresearch-integrityreview-manipulationsocial-simulation
What happened
A collection of recent arXiv submissions (CS / social and information) covering: integration of agent-based simulation and deep reinforcement learning to design misinformation-mitigation strategies; vulnerabilities and emergent risks on AI-native social platforms (Moltbook) including credential leaks (API keys, JWTs), exposed Ethereum addresses with transaction histories, and unmoderated attack discourse (SSH brute-force templates, multi-agent offensive security architectures); manipulation techniques against reputation and recommendation systems (sparse, popularity-biased review attacks) and
Why it matters
A reviewed impact interpretation has not been published for this record.
Evidence and limitations
- Source ID
- arxiv_cs_si
- Record identifier
- 396865b6b7e3ab77ba05bd53ddb0893af9437ee961ae5e79bf82088b6853a89c
- Enrichment time
- 2026-04-16T08:52:22Z
- AI-assisted enrichment
- Yes
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