5 papers
Autonomous Topology Mutation: Safe Runtime Restructuring for Multi-Agent LLM Systems with Capability, State, and Shadow Invariants
Bronislav Sidik, Chaya Levi, Nizzan Kimhi
Multi-agent LLM frameworks typically fix their team topology at boot time. When an individual agent becomes overloaded at runtime, for example by mixing too many action categories,…
MEMTIER: Tiered Memory Architecture and Retrieval Bottleneck Analysis for Long-Running Autonomous AI Agents
Bronislav Sidik, Lior Rokach
Long-running autonomous AI agents suffer from a well-documented memory coherence problem: tool-execution success rates degrade 14 percentage points over 72-hour operation windows d…
Beyond Static Sandboxing: Learned Capability Governance for Autonomous AI Agents
Bronislav Sidik, Lior Rokach
Autonomous AI agents built on open-source runtimes such as OpenClaw expose every available tool to every session by default, regardless of the task. A summarization task receives t…
3D-Anchored Lookahead Planning for Persistent Robotic Scene Memory via World-Model-Based MCTS
Bronislav Sidik, Dror Mizrahi
We present 3D-Anchored Lookahead Planning (3D-ALP), a System 2 reasoning engine for robotic manipulation that combines Monte Carlo Tree Search (MCTS) with a 3D-consistent world mod…
EWSJF: An Adaptive Scheduler with Hybrid Partitioning for Mixed-Workload LLM Inference
Bronislav Sidik, Chaya Levi, Joseph Kampeas
Serving Large Language Models (LLMs) under mixed workloads--short, latency-sensitive interactive queries alongside long, throughput-oriented batch requests--poses a fundamental sch…