
Cooperative MultiAgent Transfer Learning with LevelAdaptive Credit Assignment
Extending transfer learning to cooperative multiagent reinforcement lea...
read it

Learning to Shape Rewards using a Game of Switching Controls
Reward shaping (RS) is a powerful method in reinforcement learning (RL) ...
read it

Modelling Behavioural Diversity for Learning in OpenEnded Games
Promoting behavioural diversity is critical for solving games with nont...
read it

Online Double Oracle
Solving strategic games with huge action space is a critical yet undere...
read it

An Overview of MultiAgent Reinforcement Learning from Game Theoretical Perspective
Following the remarkable success of the AlphaGO series, 2019 was a boomi...
read it

Learning to Infer User Hidden States for Online Sequential Advertising
To drive purchase in online advertising, it is of the advertiser's great...
read it

Qvalue Path Decomposition for Deep Multiagent Reinforcement Learning
Recently, deep multiagent reinforcement learning (MARL) has become a hig...
read it

Qatten: A General Framework for Cooperative Multiagent Reinforcement Learning
In many realworld settings, a team of cooperative agents must learn to ...
read it

α^αRank: Practically Scaling αRank through Stochastic Optimisation
Recently, αRank, a graphbased algorithm, has been proposed as a soluti...
read it

α^αRank: Scalable Multiagent Evaluation through Evolution
Although challenging, strategy profile evaluation in large connected lea...
read it

Independent Generative Adversarial SelfImitation Learning in Cooperative Multiagent Systems
Many tasks in practice require the collaboration of multiple agents thro...
read it

Bilevel ActorCritic for Multiagent Coordination
Coordination is one of the essential problems in multiagent systems. Ty...
read it

Spectralbased Graph Convolutional Network for Directed Graphs
Graph convolutional networks(GCNs) have become the most popular approach...
read it

Replicaexchange NoséHoover dynamics for Bayesian learning on large datasets
In this paper, we propose a new sampler for Bayesian learning that can e...
read it

Disentangling Dynamics and Returns: Value Function Decomposition with Future Prediction
Value functions are crucial for modelfree Reinforcement Learning (RL) t...
read it

Efficient Ridesharing Order Dispatching with Mean Field MultiAgent Reinforcement Learning
A fundamental question in any peertopeer ridesharing system is how to,...
read it

MultiAgent Generalized Recursive Reasoning
We propose a new reasoning protocol called generalized recursive reasoni...
read it

Probabilistic Recursive Reasoning for MultiAgent Reinforcement Learning
Humans are capable of attributing latent mental contents such as beliefs...
read it

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...
read it

Paralleltempered Stochastic Gradient Hamiltonian Monte Carlo for Approximate Multimodal Posterior Sampling
We propose a new sampler that integrates the protocol of parallel temper...
read it

Benchmarking Deep Sequential Models on Volatility Predictions for Financial Time Series
Volatility is a quantity of measurement for the price movements of stock...
read it

Factorized QLearning for LargeScale MultiAgent Systems
Deep Qlearning has achieved a significant success in singleagent decis...
read it

Mean Field MultiAgent Reinforcement Learning
Existing multiagent reinforcement learning methods are limited typicall...
read it

Thermostatassisted Continuoustempered Hamiltonian Monte Carlo for Multimodal Posterior Sampling
In this paper, we propose a new sampling method named as the thermostat...
read it

A Study of AI Population Dynamics with Millionagent Reinforcement Learning
We conduct an empirical study on discovering the ordered collective dyna...
read it

An Empirical Study of AI Population Dynamics with Millionagent Reinforcement Learning
In this paper, we conduct an empirical study on discovering the ordered ...
read it

Adversarial Variational Inference for Tweedie Compound Poisson Models
Tweedie Compound Poisson models are heavily used for modelling nonnegat...
read it

Multiagent BidirectionallyCoordinated Nets: Emergence of Humanlevel Coordination in Learning to Play StarCraft Combat Games
Many artificial intelligence (AI) applications often require multiple in...
read it
Yaodong Yang
is this you? claim profile