Network Distributed Multi-Agent
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Cost and Accuracy of Long-Term Memory in Distributed Multi-Agent Systems Based on Large Language Models
Announce Type: replace Abstract: Long-term memory (LTM) is fundamental to large language model (LLM)-based agents in the emerging Internet of Agents (IoA), where distributed multi-agent systems (DMAS) span cloud and edge networks. Existing evaluations are typically published by framework providers and focus on token usage and latency, rarely accounting for system-level cost or deployment in DMAS. These gaps are addressed with an independent reproducible testbed that evaluates accuracy,...
Network Distributed Multi-Agent Reinforcement Learning for Consensus Control of Quadcopters
arXiv:2606.02107v1 Announce Type: new Abstract: This paper proposes a Network Distributed Multi-Agent Reinforcement Learning (ND-MARL) framework for quadcopter consensus control. Compared to conventional multi-agent MARL formulations that rely on centralized planning or fully decentralized execution, ND-MARL incorporates the swarm communication graph into the decision process. Under a 2-Neighbor communication topology, each agent observes information of only two neighbors and outputs an...
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Show HN: We post-trained a model that pen tests instead of refusing your code
I'm Dimitrios at Cosine. Quick orientation first: the read-only scan is free and you can run it right now: that's the part to try. The pen-test mode is gated behind written authorisation, because it's live offensive testing against real systems; I'll explain that below, it's not a paywall thing.