All publications

Research publications

Papers and technical reports coming out of Aresalab. Each entry below links to its HTML reader; a print-ready PDF is generated from the same source and archived alongside.

2026-04
AGENTS
Emergent Social Collaboration in Multi-Agent LLM Systems: A Mars Colony Simulation Study
Yevheniy Chuba · ARESA · YoreAI
A two-layer architecture for studying emergent collaborative behavior in multi-agent LLM systems. A deterministic rule substrate governs agent needs, pairwise bond dynamics, action selection, and a hard cost ceiling; an LLM-powered dialogue module (GPT-4o-mini / Claude Haiku) sits on top. Reproducible claims ship as experiments/run.py — stdlib Python, ~3 seconds on an M2 Pro. Across 10 seeds × 10,000 ticks we observe 3.5 ± 2.8 strong friendships, 14.6 ± 2.3 working relationships, and 3.6 ± 1.6 tensions per session, with 100% of construction sites completing (7.3 avg unique workers per site) and a 49.2% work-dominated action distribution. Cost ceiling is $0.007 per session by construction.
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PDFLive demo
Multi-Agent LLMsEmergent BehaviorGPT-4o-miniClaude Haiku
2026-04
DATABASE
AresaDB: A High-Performance Multi-Model Database in Rust
Yevheniy Chuba · ARESA · YoreAI / University of Pittsburgh
AresaDB is a high-performance, multi-model database engine written in Rust that unifies key-value, graph, and relational data paradigms under a single property graph foundation. Every cited number is reproduced by a single script in the repo. Measured on a 50K-node, 250K-edge, 10K-vector workload (macOS aarch64, April 2026 re-run against v2.0.0-alpha.2): batch insert exceeds 75,000 nodes/sec (≈258× over single inserts), point lookups land at ~5 µs p50 / 14 µs p99, HNSW search completes in ~7 µs (≈103× over brute force), and B-tree secondary indexes deliver ~23× over full-scan queries. A distributed v2 cluster (multi-Raft, range-partitioned, pluggable redb/fjall backends) is in alpha alongside this paper and is covered by a separate write-up in the same repository.
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PDFRepo
Multi-Model DatabaseProperty GraphVector SearchRAG
2026-04
ARCHIVED
Data-Driven Fire Safety Analytics: A Reproducible Audit of 550,145 Allegheny County Dispatch Records (2015-2025)
Yevheniy Chuba · ARESA · YoreAI
A reproducible audit of 550,145 fire-department dispatch records from Allegheny County (2015-2025), of which 367,444 are fire-specific. Fire alarm activations dominate the workload at 205,398 incidents (37.3% of all calls, 55.9% of fire-specific), and commercial properties account for 64% of those alarms — implying a bounded annual cost of roughly $131.5M at $1,000 per response. Structure fires peak in Winter (heating-driven) while outdoor fires peak in Spring (vegetation-driven). Every number in the paper is regenerated by experiments/run.py from the same JSON aggregations used by the archived dashboard.
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PDF
Fire SafetyEmergency ResponseDashboardData Visualization

Emergent Social Collaboration in Multi-Agent LLM Systems: A Mars Colony Simulation Study

AresaDB: A High-Performance Multi-Model Database in Rust

Data-Driven Fire Safety Analytics: A Reproducible Audit of 550,145 Allegheny County Dispatch Records (2015-2025)