This page shows the most relevant public items for Multi-Agent Systems, ranked by trend activity and review signal. Use weekly for fast changes, monthly for more stable patterns, and all-time for evergreen picks.
Paper • Aug 8, 2025 • arXiv • Jian Lu, Percy Liang, Chelsea Finn
While scaling laws for single-model LLMs are well established, the relationship between the number of collaborating agents and overall system performance remains poorly understood. This paper inves...
Paper • Jun 7, 2017 • arXiv • Ryan Lowe, Yi Wu, Aviv Tamar, Jean Harb, Pieter Abbeel, Igor Mordatch
We explore deep reinforcement learning methods for multi-agent domains. We begin by analyzing the difficulty of traditional algorithms in the multi-agent case: Q-learning is challenged by an inhere...
Paper • Sep 17, 2019 • arXiv • Bowen Baker, Ingmar Kanitscheider, Todor Markov, Yi Wu, Glenn Powell, Bob McGrew, Igor Mordatch
We demonstrate that simple multi-agent competition can drive the emergence of highly complex, intelligent behaviors without explicit human design. We train agents using reinforcement learning to pl...
Paper • May 31, 2019 • Science • Max Jaderberg, Wojciech M. Czarnecki, Iain Dunning, Luke Marris, Guy Lever, Antonio Garcia Castaneda, Charles Beattie, Neil C. Rabinowitz, Ari S. Morcos, Avraham Ruderman, Nicolas Sonnerat, Tim Green, Louise Deason, Joel Z. Leibo, David Silver, Demis Hassabis, Koray Kavukcuoglu, Thore Graepel
Multiplayer video games represent a significant frontier for AI research, requiring real-time, high-dimensional sensory processing, spatial navigation, and team-based coordination. We report an AI ...
Paper • Feb 23, 2026 • arXiv • Susan Athey, Michael I. Jordan
The proliferation of personal autonomous agents capable of executing micro-transactions, negotiating contracts, and performing high-speed arbitrage threatens to upend traditional market stability. ...
Paper • Feb 20, 2026 • bioRxiv • L. Zheng, J. Drucker, A. Chen, W. Wang
Designing therapeutic peptides requires balancing binding affinity with complex ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties, a task that overwhelms traditional ...
Paper • Feb 18, 2026 • arXiv • Siddharth V., Elena K., Marcus W., Yujin H.
As agents increasingly handle high-stakes tasks like financial transactions and system permissions, the mechanism of 'Authority Transfer' becomes a critical attack surface. We introduce the Agent-i...
Paper • Apr 16, 2025 • arXiv • Yannick LeCun, Antoine Bordes, Elena Rossi, Marcus Thorne
The propensity of large language models to hallucinate facts severely limits their deployment in autonomous agentic workflows where verification is costly. This paper introduces 'Agentic Debate,' a...
Paper • May 15, 2025 • arXiv • Ranjan Sapkota, Konstantinos I. Roumeliotis, Manoj Karkee
This review critically distinguishes between traditional 'AI Agents' and the broader paradigm of 'Agentic AI', offering a structured conceptual taxonomy and application mapping. The authors argue t...
Paper • Oct 30, 2019 • Nature • Oriol Vinyals, Igor Babuschkin, Wojciech M. Czarnecki, Michaël Mathieu, Andrew Dudzik, David Silver
The game of StarCraft II has emerged as a grand challenge for artificial intelligence research owing to its complex, multi-agent, and partially observable environment. Here we introduce AlphaStar, ...
Paper • Feb 12, 2026 • arXiv • Nenad Tomašev, Kevin R. McKee, Jack Rae, Iason Gabriel, Vukosi Marivate, Milind Tambe, Demis Hassabis, Charles Blundell
As advanced AI agents evolve beyond query-response models, their utility is increasingly defined by how effectively they can decompose complex objectives and delegate sub-tasks. We propose an adapt...
Paper • Feb 16, 2026 • arXiv • Mingju Chen, Guibin Zhang, Heng Chang, Yuchen Guo
Traditional multi-agent systems often struggle with 'search breadth' in unstructured environments, leading to tunnel vision in reasoning. We propose A-MapReduce, a framework that applies the MapRed...
Paper • Feb 18, 2026 • arXiv • Jianhao Ruan, et al.
Language agents have shown strong promise for task automation, but realizing this promise for increasingly complex, long-horizon tasks has driven the rise of a sub-agent-as-tools paradigm. However,...
Paper • Feb 28, 2026 • arXiv • Virginia Dignum, Frank Dignum
The rapid popularization of the term 'Agentic AI' has led to semantic confusion, often blurring the lines between simple generative loops and true software agency. This position paper critically ex...
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