AITopics | Results of multi-agent system and ontology to manage …
This article is about an intelligent system to support ideas management as a result of a multi-agent system used in a distributed system with heterogeneous information as ideas and …
Multi-Agent Reinforcement Learning for Autonomous Driving: A …
Reinforcement Learning (RL) is a potent tool for sequential decision-making and has achieved performance surpassing human capabilities across many challenging real-world tasks. As the …
An Overview of Multi-Agent Reinforcement Learning from Game …
MARL corresponds to the learning problem in a multi-agent system in which multiple agents learn simultaneously. MARL is an interdisciplinary domain with a long history that includes game …
AITopics | transient behavior
Oct 16, 2023 · Robust Integral Consensus Control of Multi-Agent Networks Perturbed by Matched and Unmatched Disturbances: The Case of Directed Graphs Romero, Jose Guadalupe, …
AITopics | A Survey on LLM-powered Agents for Recommender …
Recommender systems are essential components of many online platforms, yet traditional approaches still struggle with understanding complex user preferences and providing …
AITopics | Multi-Agent Verification: Scaling Test-Time Compute …
We introduce Multi-Agent Verification (MAV) as a test-time compute paradigm that combines multiple verifiers to improve performance. We propose using Aspect Verifiers (AVs), off-the …
Boosting Studies of Multi-Agent Reinforcement Learning on …
Even though Google Research Football (GRF) was initially benchmarked and studied as a single-agent environment in its original paper, recent years have witnessed an increasing focus on its …
AITopics | Learning Others' Intentional Models in Multi-Agent …
Apr 6, 2018 · Interactive partially observable Markov decision processes (I-POMDPs) provide a principled framework for planning and acting in a partially observable, stochastic and multi …
AITopics | complexity level
Nov 19, 2025 · Large language models (LLMs) based agent systems have made great strides in real-world applications beyond traditional NLP tasks. This paper proposes a new LLM …
AITopics | Multi-Agent Reinforcement Learning via Mean Field …
Recently, mean field control (MFC) has provided a tractable and theoretically founded approach to otherwise difficult cooperative multi-agent control. However, the strict assumption of many …