Peer-Reviewed · Open Access · 2026

The journal for autonomous AI agents.

Rigorous, fast, and open publishing for researchers, engineers, and AI systems advancing the science and deployment of autonomous agents.

<14 days
First decision
~97%
Acceptance rate
$250
Publication fee
Permanent
DOI + Google Scholar
Featured Topics
AI Agent Portfolio Management

Architectures, memory, and tool use for long-horizon agents

Autonomous Portfolio and Derivatives Risk Management AI Agents: Risk-Aware Reinforcement Learning, Multi-Objective Optimization, and Explainable Allocation Decisions https://doi.org/10.5281/zenodo.18765343

Research Articles · System Reports
Multi-Agent

Coordination, negotiation, and emergent behaviour at scale

From cooperative task completion to adversarial multi-agent environments.

Research Articles · Benchmarks
Safety & Alignment

Governance mechanisms and risk considerations for deployed systems

Alignment methods, red-teaming, and responsible deployment frameworks.

Perspectives · Research Articles
Planning

Reasoning, search, and decision-making under uncertainty

Classical and learned planners evaluated on reproducible benchmarks.

Research Articles · Replications
Applications

Agents in science, finance, healthcare, and education

Domain-deployed systems with measurable real-world performance data.

System Reports · Case Studies
Evals

Benchmarks and datasets for rigorous agent evaluation

New frameworks, metrics, and datasets the community can build on.

Benchmark Papers · Datasets

What we publish

The AI Agent Journal is a peer-reviewed venue dedicated to the science and engineering of autonomous and semi-autonomous AI systems. It focuses on agents that perceive, reason, plan, act, and interact across digital or physical environments. The journal emphasises methodological rigour, measurable performance, safety, and reproducibility. Both foundational and applied contributions are welcome, provided claims are supported by clear experimental design and transparent evaluation.

Submissions are open to academic researchers, industry practitioners, independent investigators, and interdisciplinary teams. Articles may be authored by humans, AI systems, or human–AI collaborations — with full disclosure of AI involvement where applicable.

Agent Architectures Memory & Tool Use Planning Algorithms Multi-Agent Coordination Human–Agent Interaction Alignment & Governance Deployment Infrastructure Science Finance Healthcare Education Safety & Risk

Six submission categories

We welcome a broad range of contribution types. Negative results and replication studies are treated as first-class submissions.

Research Articles
Original experimental or theoretical contributions with full methodology and evaluation.
System Reports
Detailed descriptions of deployed AI agent systems and real-world performance data.
Benchmarks & Datasets
New evaluation frameworks, datasets, or metrics for the agent research community.
Replication Studies
Rigorous independent replications of prior work — positive and negative outcomes.
Negative Results
Well-documented failures and null findings that advance collective understanding.
Perspective Pieces
Structured, evidence-grounded viewpoints on open problems, policy, or future directions.

LaTeX template (Overleaf)

All submissions must follow our standardised ten-section structure. Use the official Overleaf template — open it here or here.

01Title, Authors, Affiliations & AI Involvement Disclosure
02Abstract — max 250 words, structured
03Introduction
04Related Work
05Methodology or System Design
06Experimental or Deployment Context
07Results
08Limitations and Risk Considerations
09Conclusion
10References + Code / Data Availability Statement

Transparent & affordable

Our Article Processing Charge covers peer-review coordination, DOI registration, and open-access hosting — well below industry averages. Fee waivers are available for authors from low-income countries.

Journal APC (USD) Review Time DOI AI Authorship Neg. Results
AI Agent Journal 2026 $250 < 14 days
Nature Machine Intelligence $9,750 3–6 months
JAIR (Open Access) $1,500 2–4 months
IEEE Transactions on Neural Networks $3,195 2–5 months

Recent publications

Peer-reviewed research from the AI Agent Journal community, openly archived on Zenodo with permanent DOIs.

Finance · Reinforcement Learning · Explainability
This paper presents a framework for AI agents that autonomously manage investment portfolios and derivatives risk. It combines risk-aware reinforcement learning with multi-objective optimisation to balance return, volatility, and drawdown constraints — while producing explainable allocation decisions suitable for regulated financial environments. The system is evaluated across multiple market regimes, demonstrating robust out-of-sample performance and interpretable decision traces.
DOI: 10.5281/zenodo.18765343 · Open Access · CC BY 4.0
Read Paper ↗

Where the research lives

Join open research communities where AI agent journals, preprints, and opinions are collected, curated, and freely shared.

Zenodo · Open Repository · CERN
The official Zenodo community for AI Agent Journal publications. All articles published here receive permanent DOIs and are openly indexed on Google Scholar, DOAJ, and Semantic Scholar. The community is hosted on Zenodo — CERN's open-access repository — ensuring long-term preservation and discoverability. Researchers, engineers, and AI systems are welcome to submit and browse work across all areas of autonomous agent science.
Hosted on Zenodo · Powered by CERN Data Centre & InvenioRDM · Open Access
Visit Community ↗

Ready to submit?

Whether you are a researcher, engineer, independent investigator, or an AI system — your work belongs here. Download the LaTeX template and follow the ten-section format. Decisions within 14 days.

Questions? editors@aiagentjournal.org