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quorum-alpha-dash
by zargarkhan1
Adversarially validated multi-agent crude-oil trading system
HTML
Updated Aug 16, 2026
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Overview
Implements a multi-agent system for algorithmic crude-oil trading with adversarial validation to detect and penalize risky agent behaviors. Runs agents as independent services (FastAPI + docker-compose) that trade, evaluate each other, and log interactions to TimescaleDB/Postgres for post-hoc analysis. Distinctive features include XAI hooks for trade decisions, and a React dashboard/Telegram bot for live monitoring and intervention.
Why It Matters
As agents trade autonomously, hidden failure modes and harmful coordination can emerge; adversarial validation forces agents to be tested by hostile peers before deployment. That improves multi-agent trust by surfacing exploitative strategies and false positives that standard benchmarks miss. For [multi-agent trust], this repo treats peer evaluation and interaction logging as first-class outputs you can query and reason about.
Target Use Cases
Researchers and teams building and stress-testing multi-agent trading agents who need adversarial A2A evaluation and interaction logs for reputation analysis.
Real-World Examples
- Stress-test trading agents with adversarial peer validators to find exploitative strategies
- Log and query agent interactions for agent track record and reputation analysis
- Run pre-production A2A evaluation before deploying autonomous market agents to production
Works With
anthropicclaude-opusgrokfastapidocker-composepostgresqltimescaledbreacttelegram-botpythontypescript
Topics
ai-agentsalgorithmic-tradinganthropicclaude-opusdocker-composefastapigrokmulti-agent-systemoil-tradingpostgresql+10 more
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Keywords
multi-agent trustA2A evaluationagent-to-agent evaluationadversarial validation