The field of artificial intelligence is witnessing significant advancements in agentic AI and multi-agent systems. Recent developments have focused on creating autonomous agents that can collaborate, make decisions, and interact with humans in a more efficient and trustworthy manner. Researchers are exploring the use of blockchain-enabled architectures, explainable AI, and transparent decision-making processes to enhance the security and reliability of multi-agent systems. Notable papers in this area have proposed novel frameworks for regulatory agent collaboration, trustworthy agentic IoEV, and secure multi-agent systems. These advancements have the potential to transform various domains, including finance, healthcare, and transportation, by enabling more efficient, scalable, and secure interactions between humans and AI agents. Noteworthy papers include: Enabling Regulatory Multi-Agent Collaboration, which proposes a blockchain-enabled layered architecture for regulatory agent collaboration. Sentinel Agents for Secure and Trustworthy Agentic AI in Multi-Agent Systems, which presents a novel architectural framework aimed at enhancing security and reliability in multi-agent systems.
Advancements in Agentic AI and Multi-Agent Systems
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Anti-Money Laundering Machine Learning Pipelines; A Technical Analysis on Identifying High-risk Bank Clients with Supervised Learning
Enabling Regulatory Multi-Agent Collaboration: Architecture, Challenges, and Solutions
PARROT: Portable Android Reproducible traffic Observation Tool
GAMA: A General Anonymizing Multi-Agent System for Privacy Preservation Enhanced by Domain Rules and Disproof Method
Virtual Agent Economies
We Need a New Ethics for a World of AI Agents
Towards Trustworthy Agentic IoEV: AI Agents for Explainable Cyberthreat Mitigation and State Analytics
Funding AI for Good: A Call for Meaningful Engagement
Redefining CX with Agentic AI: Minerva CQ Case Study
Match Chat: Real Time Generative AI and Generative Computing for Tennis
DoubleAgents: Exploring Mechanisms of Building Trust with Proactive AI
The Impact of Automation on Risk-Taking: The Role of Sense of Agency
Agentic AI for Financial Crime Compliance
Early Approaches to Adversarial Fine-Tuning for Prompt Injection Defense: A 2022 Study of GPT-3 and Contemporary Models
A Multi-Agent LLM Defense Pipeline Against Prompt Injection Attacks
Why Johnny Can't Use Agents: Industry Aspirations vs. User Realities with AI Agent Software
Threat Modeling for Enhancing Security of IoT Audio Classification Devices under a Secure Protocols Framework
Sentinel Agents for Secure and Trustworthy Agentic AI in Multi-Agent Systems