A review of cooperation in multi-agent learning
Cooperation in multi-agent learning (MAL) is a topic at the intersection of numerous
disciplines, including game theory, economics, social sciences, and evolutionary biology …
disciplines, including game theory, economics, social sciences, and evolutionary biology …
多智能体博弈学习研究进展.
罗俊仁， 张万鹏， 苏炯铭， 袁唯淋… - Systems Engineering & …, 2024 - search.ebscohost.com
随着深度学习和强化学习而来的人工智能新浪潮, 为智能体从感知输入到行动决策输出提供了“
端到端” 解决方案. 多智能体学习是研究智能博弈对抗的前沿课题, 面临着对抗性环境 …
端到端” 解决方案. 多智能体学习是研究智能博弈对抗的前沿课题, 面临着对抗性环境 …
[图书][B] Multi-agent reinforcement learning: Foundations and modern approaches
The first comprehensive introduction to Multi-Agent Reinforcement Learning (MARL),
covering MARL's models, solution concepts, algorithmic ideas, technical challenges, and …
covering MARL's models, solution concepts, algorithmic ideas, technical challenges, and …
Game Plan: What AI can do for Football, and What Football can do for AI
The rapid progress in artificial intelligence (AI) and machine learning has opened
unprecedented analytics possibilities in various team and individual sports, including …
unprecedented analytics possibilities in various team and individual sports, including …
Real world games look like spinning tops
This paper investigates the geometrical properties of real world games (eg Tic-Tac-Toe, Go,
StarCraft II). We hypothesise that their geometrical structure resembles a spinning top, with …
StarCraft II). We hypothesise that their geometrical structure resembles a spinning top, with …
Strategic knowledge transfer
In the course of playing or solving a game, it is common to face a series of changing other-
agent strategies. These strategies often share elements: the set of possible policies to play …
agent strategies. These strategies often share elements: the set of possible policies to play …
Navigating the landscape of multiplayer games
Multiplayer games have long been used as testbeds in artificial intelligence research, aptly
referred to as the Drosophila of artificial intelligence. Traditionally, researchers have focused …
referred to as the Drosophila of artificial intelligence. Traditionally, researchers have focused …
A Meta-Game Evaluation Framework for Deep Multiagent Reinforcement Learning
Z Li, MP Wellman - arXiv preprint arXiv:2405.00243, 2024 - arxiv.org
Evaluating deep multiagent reinforcement learning (MARL) algorithms is complicated by
stochasticity in training and sensitivity of agent performance to the behavior of other agents …
stochasticity in training and sensitivity of agent performance to the behavior of other agents …
[PDF][PDF] Fraud risk mitigation in real-time payments: A strategic agent-based analysis
Whereas standard financial mechanisms for payment may take days to finalize, real-time
payments (RTPs) provide immediate processing and final receipt of funds. The speed of …
payments (RTPs) provide immediate processing and final receipt of funds. The speed of …
Robust risk-sensitive reinforcement learning agents for trading markets
Y Gao, KYC Lui, P Hernandez-Leal - arXiv preprint arXiv:2107.08083, 2021 - arxiv.org
Trading markets represent a real-world financial application to deploy reinforcement
learning agents, however, they carry hard fundamental challenges such as high variance …
learning agents, however, they carry hard fundamental challenges such as high variance …