DeepYard
A

ATLAS

LLM-powered automata learning for analyzing and explaining agent strategies

Open SourceFree

About

ATLAS uses LLM-guided abstraction to discover and explain agent strategies through automata learning. Designed for researchers and developers working with complex autonomous agents, it automatically extracts interpretable behavioral patterns from agent trajectories. Particularly useful for debugging multi-agent systems and understanding emergent behaviors in reinforcement learning environments.

Details

Type
Integrations
Language

Tags

autonomousobservabilityevaluationmulti-agentopen-sourcepython