Deep Intentions
Boosting agent orchestration in MCP environments by refining decision-making for communication timing and cross-interaction coherence.
Project Description
Our project combines Belief-Desire-Intention (BDI) architecture with modern LLM-based Agentic AI to create multi-agent systems that excel in dynamic, complex environments like emergency response and disaster management. While existing Agentic AI solutions struggle in rapidly changing conditions, our approach enables sophisticated coordination between different agents, seamless integration with various tools and technologies, and most critically - full transparency in decision-making processes.
The Problem: In complex environments, decisions must be made quickly, accurately, and in coordination across multiple teams. Current AI systems lack the mental models needed to operate effectively in these dynamic environments. Moreover, the existing Agentic AI ecosystem was not engineered to accommodate this and is essentially pipeline/workflow oriented.
Our Solution: Deep Intentions provides a revolutionary framework that combines traditional BDI agent architecture with cutting-edge LLM capabilities. This unique integration gives virtual agents the mental models they need to reason effectively in complex, changing environments.
Prior Work
The idea has been in mind for about a year, but all deliverables were created during this hackathon event.
Team
Products & Tools
Additional Links
Git repository containing all code deliverables see README for overview of demoable components