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06/01/2021
Cooperative Multi-Agent Transfer Learning with Level-Adaptive Credit Assignment
Extending transfer learning to cooperative multi-agent reinforcement lea...
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03/16/2021
Learning to Shape Rewards using a Game of Switching Controls
Reward shaping (RS) is a powerful method in reinforcement learning (RL) ...
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03/14/2021
Modelling Behavioural Diversity for Learning in Open-Ended Games
Promoting behavioural diversity is critical for solving games with non-t...
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03/13/2021
Online Double Oracle
Solving strategic games with huge action space is a critical yet under-e...
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11/01/2020
An Overview of Multi-Agent Reinforcement Learning from Game Theoretical Perspective
Following the remarkable success of the AlphaGO series, 2019 was a boomi...
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09/03/2020
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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02/10/2020
Q-value Path Decomposition for Deep Multiagent Reinforcement Learning
Recently, deep multiagent reinforcement learning (MARL) has become a hig...
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02/10/2020
Qatten: A General Framework for Cooperative Multiagent Reinforcement Learning
In many real-world settings, a team of cooperative agents must learn to ...
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09/25/2019
α^α-Rank: Practically Scaling α-Rank through Stochastic Optimisation
Recently, α-Rank, a graph-based algorithm, has been proposed as a soluti...
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09/25/2019
α^α-Rank: Scalable Multi-agent Evaluation through Evolution
Although challenging, strategy profile evaluation in large connected lea...
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09/25/2019
Independent Generative Adversarial Self-Imitation Learning in Cooperative Multiagent Systems
Many tasks in practice require the collaboration of multiple agents thro...
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09/08/2019
Bi-level Actor-Critic for Multi-agent Coordination
Coordination is one of the essential problems in multi-agent systems. Ty...
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07/21/2019
Spectral-based Graph Convolutional Network for Directed Graphs
Graph convolutional networks(GCNs) have become the most popular approach...
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05/29/2019
Replica-exchange Nosé-Hoover 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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05/27/2019
Disentangling Dynamics and Returns: Value Function Decomposition with Future Prediction
Value functions are crucial for model-free Reinforcement Learning (RL) t...
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01/31/2019
Efficient Ridesharing Order Dispatching with Mean Field Multi-Agent Reinforcement Learning
A fundamental question in any peer-to-peer ridesharing system is how to,...
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01/26/2019
Multi-Agent Generalized Recursive Reasoning
We propose a new reasoning protocol called generalized recursive reasoni...
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01/26/2019
Probabilistic Recursive Reasoning for Multi-Agent Reinforcement Learning
Humans are capable of attributing latent mental contents such as beliefs...
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12/14/2018
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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12/04/2018
Parallel-tempered 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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11/08/2018
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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09/11/2018
Factorized Q-Learning for Large-Scale Multi-Agent Systems
Deep Q-learning has achieved a significant success in single-agent decis...
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02/15/2018
Mean Field Multi-Agent Reinforcement Learning
Existing multi-agent reinforcement learning methods are limited typicall...
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11/30/2017
Thermostat-assisted Continuous-tempered Hamiltonian Monte Carlo for Multimodal Posterior Sampling
In this paper, we propose a new sampling method named as the thermostat-...
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09/13/2017
A Study of AI Population Dynamics with Million-agent Reinforcement Learning
We conduct an empirical study on discovering the ordered collective dyna...
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09/13/2017
An Empirical Study of AI Population Dynamics with Million-agent Reinforcement Learning
In this paper, we conduct an empirical study on discovering the ordered ...
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06/16/2017
Adversarial Variational Inference for Tweedie Compound Poisson Models
Tweedie Compound Poisson models are heavily used for modelling non-negat...
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03/29/2017