
An Overview of MultiAgent Reinforcement Learning from Game Theoretical Perspective
Following the remarkable success of the AlphaGO series, 2019 was a boomi...
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Learning to Infer User Hidden States for Online Sequential Advertising
To drive purchase in online advertising, it is of the advertiser's great...
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Qvalue Path Decomposition for Deep Multiagent Reinforcement Learning
Recently, deep multiagent reinforcement learning (MARL) has become a hig...
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Qatten: A General Framework for Cooperative Multiagent Reinforcement Learning
In many realworld settings, a team of cooperative agents must learn to ...
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α^αRank: Practically Scaling αRank through Stochastic Optimisation
Recently, αRank, a graphbased algorithm, has been proposed as a soluti...
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α^αRank: Scalable Multiagent Evaluation through Evolution
Although challenging, strategy profile evaluation in large connected lea...
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Independent Generative Adversarial SelfImitation Learning in Cooperative Multiagent Systems
Many tasks in practice require the collaboration of multiple agents thro...
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Bilevel ActorCritic for Multiagent Coordination
Coordination is one of the essential problems in multiagent systems. Ty...
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Spectralbased Graph Convolutional Network for Directed Graphs
Graph convolutional networks(GCNs) have become the most popular approach...
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Replicaexchange NoséHoover dynamics for Bayesian learning on large datasets
In this paper, we propose a new sampler for Bayesian learning that can e...
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Disentangling Dynamics and Returns: Value Function Decomposition with Future Prediction
Value functions are crucial for modelfree Reinforcement Learning (RL) t...
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Efficient Ridesharing Order Dispatching with Mean Field MultiAgent Reinforcement Learning
A fundamental question in any peertopeer ridesharing system is how to,...
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MultiAgent Generalized Recursive Reasoning
We propose a new reasoning protocol called generalized recursive reasoni...
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Probabilistic Recursive Reasoning for MultiAgent Reinforcement Learning
Humans are capable of attributing latent mental contents such as beliefs...
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Can Deep Learning Predict Risky Retail Investors? A Case Study in Financial Risk Behavior Forecasting
The success of deep learning for unstructured data analysis is well docu...
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Paralleltempered Stochastic Gradient Hamiltonian Monte Carlo for Approximate Multimodal Posterior Sampling
We propose a new sampler that integrates the protocol of parallel temper...
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Benchmarking Deep Sequential Models on Volatility Predictions for Financial Time Series
Volatility is a quantity of measurement for the price movements of stock...
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Factorized QLearning for LargeScale MultiAgent Systems
Deep Qlearning has achieved a significant success in singleagent decis...
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Mean Field MultiAgent Reinforcement Learning
Existing multiagent reinforcement learning methods are limited typicall...
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Thermostatassisted Continuoustempered Hamiltonian Monte Carlo for Multimodal Posterior Sampling
In this paper, we propose a new sampling method named as the thermostat...
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A Study of AI Population Dynamics with Millionagent Reinforcement Learning
We conduct an empirical study on discovering the ordered collective dyna...
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An Empirical Study of AI Population Dynamics with Millionagent Reinforcement Learning
In this paper, we conduct an empirical study on discovering the ordered ...
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Adversarial Variational Inference for Tweedie Compound Poisson Models
Tweedie Compound Poisson models are heavily used for modelling nonnegat...
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Multiagent BidirectionallyCoordinated Nets: Emergence of Humanlevel Coordination in Learning to Play StarCraft Combat Games
Many artificial intelligence (AI) applications often require multiple in...
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Yaodong Yang
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