References
Foundational Papers and Research
Seminal Works on AI Agents
- "Intelligent Agents: Theory and Practice" - Wooldridge & Jennings (1995)
- "Agent-Oriented Software Engineering" - Jennings (2000)
- "Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence" - Ferber (1999)
Recent Advances in Agentic AI
- "ReAct: Synergizing Reasoning and Acting in Language Models" - Yao et al. (2022)
- "Toolformer: Language Models Can Teach Themselves to Use Tools" - Schick et al. (2023)
- "AutoGPT: An Autonomous GPT-4 Experiment" - Significant Games (2023)
Industry Standards and Specifications
Protocols and Standards
- Model Context Protocol (MCP) - Anthropic
- Agent2Agent (A2A) Protocol - Multi-vendor collaboration
- AGENTS.md Specification - Agent description standard
- OpenSpec - Open agent specification framework
Framework Documentation
- LangChain Documentation - Comprehensive agent framework
- LangGraph Documentation - Graph-based agent workflows
- AutoGen Documentation - Microsoft's multi-agent framework
- CrewAI Documentation - Role-based multi-agent systems
Academic Resources
Research Institutions
- Stanford HAI - Human-Centered AI Institute
- MIT CSAIL - Computer Science and Artificial Intelligence Laboratory
- DeepMind - Advanced AI research
- OpenAI - AI safety and capability research
Conferences and Journals
- AAMAS - International Conference on Autonomous Agents and Multi-Agent Systems
- IJCAI - International Joint Conference on Artificial Intelligence
- NeurIPS - Conference on Neural Information Processing Systems
- ICML - International Conference on Machine Learning
Industry Resources
Vendor Documentation
- AWS Bedrock Agents - Cloud-native agent services
- Google Gemini Enterprise Agent Platform - Enterprise agent platform (formerly Vertex AI Agent Builder)
- Microsoft Agent Framework - .NET-based agent development
- Anthropic Claude - Constitutional AI and safety research
Open Source Projects
- LangChain - Python/JavaScript agent framework
- AutoGen - Multi-agent conversation framework
- Haystack - NLP pipeline and agent framework
- Semantic Kernel - Microsoft's AI orchestration SDK
Books and Publications
Technical Books
- "Artificial Intelligence: A Modern Approach" - Russell & Norvig
- "Multi-Agent Systems" - Weiss (Editor)
- "Programming Multi-Agent Systems" - Bordini et al.
Industry Reports
- Gartner AI Hype Cycle - Annual technology maturity assessment
- McKinsey AI Report - Business impact and adoption trends
- Deloitte AI Survey - Enterprise AI implementation insights
Online Resources
Documentation Portals
- LangChain Documentation
- OpenAI API Documentation
- Anthropic Claude Documentation
- Google AI Documentation
Community Resources
- GitHub Repositories - Open source agent implementations
- Hugging Face - Model and dataset repositories
- Papers with Code - Research paper implementations
- AI/ML Conferences - Latest research presentations
Latest Research and Developments
ArXiv Papers
- Agentic AI-Driven Technical Troubleshooting for Enterprise Systems
- Microsoft ExACT: Improving AI agents' decision-making via test-time compute scaling
- Google - Chain of Agents: Large language models collaborating on long-context tasks
- RouteLLM - Learning to Route LLMs with Preference Data
- Agentic AI-Driven Technical Troubleshooting for RAG Paradigm
Google Research
OpenAI Research
Foundational Research
Source: Agent AI Towards a Holistic Intelligence