Building Scalable Multi-Agent Systems(MAS) Using GripTape
Multi-agent systems (MAS) represent a transformative approach in artificial intelligence, where multiple autonomous agents collaborate to solve complex problems and ...
Tag: multiagent
AutoCBT: A Multi-Agent Adaptive Framework for Enhanced Automated Cognitive Behavioral Therapy
Traditional psychological counseling, which is often done in person, remains limited to people who are actively seeking help for psychological ...
Swarm: A Complete Guide to Lightweight Multi-Agent Orchestration for Scalable and Dynamic Workflows with Code Deployment
Swarm is an innovative open source framework designed to explore the orchestration and coordination of multi-agent systems. It is developed ...
Unlocking complex problem-solving with multi-agent collaboration on Amazon Bedrock
Large language model (LLM) based ai agents that have been specialized for specific tasks have demonstrated great problem-solving capabilities. By ...
Democratizing AI: Deploying an LLM-Based Multimodal Multi-Agent System with No-Code Platforms for Business Automation
The adoption of advanced ai technologies, including LLM-powered multi-agent systems (MAS), presents significant challenges for organizations due to high technical ...
REDA: A new AI approach to multi-agent reinforcement learning that makes complex sequence-dependent assignment problems solvable
Power distribution systems are often conceptualized as optimization models. While optimizing agents to perform tasks works well in systems with ...
Design multi-agent orchestration with reasoning using Amazon Bedrock and open source frameworks
As generative ai capabilities evolve, successful business adoptions hinge on the development of robust problem-solving capabilities. At the forefront of ...
MosAIC: A multi-agent AI framework for cross-cultural image captioning
Large multimodal models (LMMs) excel in many vision and language tasks, but their effectiveness needs to improve in cross-cultural contexts. ...
Splunk Researchers Introduce MAG-V: A Multi-Agent Framework for Synthetic Data Generation and Reliable AI Trajectory Verification
Today, large language models (LLM) are being integrated with multi-agent systems, where multiple intelligent agents collaborate to achieve a unified ...
Bridging neural dynamics and collective intelligence: A study on adaptive multi-agent systems for effective consensus building in complex and dynamic environments
The study of collective decision making in biological and artificial systems addresses critical challenges to understanding how groups achieve consensus ...
