research
∙
10/05/2022
Game Theoretic Rating in N-player general-sum games with Equilibria
Rating strategies in a game is an important area of research in game the...
share
research
∙
02/15/2022
NeuPL: Neural Population Learning
Learning in strategy games (e.g. StarCraft, poker) requires the discover...
research
∙
01/05/2022
Hidden Agenda: a Social Deduction Game with Diverse Learned Equilibria
A key challenge in the study of multiagent cooperation is the need for i...
research
∙
09/28/2021
A PAC-Bayesian Analysis of Distance-Based Classifiers: Why Nearest-Neighbour works!
Abstract We present PAC-Bayesian bounds for the generalisation error of ...
research
∙
07/14/2021
Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Pot
Existing evaluation suites for multi-agent reinforcement learning (MARL)...
research
∙
06/17/2021
Multi-Agent Training beyond Zero-Sum with Correlated Equilibrium Meta-Solvers
Two-player, constant-sum games are well studied in the literature, but t...
research
∙
05/25/2021
From Motor Control to Team Play in Simulated Humanoid Football
Intelligent behaviour in the physical world exhibits structure at multip...
research
∙
03/08/2021
Deep reinforcement learning models the emergent dynamics of human cooperation
Collective action demands that individuals efficiently coordinate how mu...
research
∙
02/08/2021
EigenGame Unloaded: When playing games is better than optimizing
We build on the recently proposed EigenGame that views eigendecompositio...
research
∙
12/15/2020
Open Problems in Cooperative AI
Problems of cooperation–in which agents seek ways to jointly improve the...
research
∙
11/18/2020
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 ...
research
∙
10/20/2020
Negotiating Team Formation Using Deep Reinforcement Learning
When autonomous agents interact in the same environment, they must often...
research
∙
10/18/2020
Model-free conventions in multi-agent reinforcement learning with heterogeneous preferences
Game theoretic views of convention generally rest on notions of common k...
research
∙
10/01/2020
EigenGame: PCA as a Nash Equilibrium
We present a novel view on principal component analysis (PCA) as a compe...
research
∙
06/08/2020
Learning to Play No-Press Diplomacy with Best Response Policy Iteration
Recent advances in deep reinforcement learning (RL) have led to consider...
research
∙
01/14/2020
Smooth markets: A basic mechanism for organizing gradient-based learners
With the success of modern machine learning, it is becoming increasingly...
research
∙
12/11/2019
Biases for Emergent Communication in Multi-agent Reinforcement Learning
We study the problem of emergent communication, in which language arises...
research
∙
11/19/2019
Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model
Constructing agents with planning capabilities has long been one of the ...
research
∙
09/27/2019
A Generalized Training Approach for Multiagent Learning
This paper investigates a population-based training regime based on game...
research
∙
07/11/2019
A Neural Architecture for Designing Truthful and Efficient Auctions
Auctions are protocols to allocate goods to buyers who have preferences ...
research
∙
05/13/2019
Differentiable Game Mechanics
Deep learning is built on the foundational guarantee that gradient desce...
research
∙
03/02/2019
Autocurricula and the Emergence of Innovation from Social Interaction: A Manifesto for Multi-Agent Intelligence Research
Evolution has produced a multi-scale mosaic of interacting adaptive unit...
research
∙
02/19/2019
Emergent Coordination Through Competition
We study the emergence of cooperative behaviors in reinforcement learnin...
research
∙
01/23/2019
Open-ended Learning in Symmetric Zero-sum Games
Zero-sum games such as chess and poker are, abstractly, functions that e...
research
∙
12/17/2018
Malthusian Reinforcement Learning
Here we explore a new algorithmic framework for multi-agent reinforcemen...
research
∙
09/28/2018
Relational Forward Models for Multi-Agent Learning
The behavioral dynamics of multi-agent systems have a rich and orderly s...
research
∙
07/03/2018
Human-level performance in first-person multiplayer games with population-based deep reinforcement learning
Recent progress in artificial intelligence through reinforcement learnin...
research
∙
06/11/2018
Adaptive Mechanism Design: Learning to Promote Cooperation
In the future, artificial learning agents are likely to become increasin...
research
∙
06/07/2018
Re-evaluating evaluation
Progress in machine learning is measured by careful evaluation on proble...
research
∙
03/23/2018
Inequity aversion improves cooperation in intertemporal social dilemmas
Groups of humans are often able to find ways to cooperate with one anoth...
research
∙
03/23/2018
Inequity aversion resolves intertemporal social dilemmas
Groups of humans are often able to find ways to cooperate with one anoth...
research
∙
03/16/2018
A Generalised Method for Empirical Game Theoretic Analysis
This paper provides theoretical bounds for empirical game theoretical an...
research
∙
02/15/2018
The Mechanics of n-Player Differentiable Games
The cornerstone underpinning deep learning is the guarantee that gradien...
research
∙
12/05/2017
Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
The game of chess is the most widely-studied domain in the history of ar...
research
∙
11/14/2017
Symmetric Decomposition of Asymmetric Games
We introduce new theoretical insights into two-population asymmetric gam...
research
∙
11/02/2017
A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning
To achieve general intelligence, agents must learn how to interact with ...
research
∙
07/20/2017
A multi-agent reinforcement learning model of common-pool resource appropriation
Humanity faces numerous problems of common-pool resource appropriation. ...
research
∙
06/16/2017
Value-Decomposition Networks For Cooperative Multi-Agent Learning
We study the problem of cooperative multi-agent reinforcement learning w...
research
∙
02/10/2017
Multi-agent Reinforcement Learning in Sequential Social Dilemmas
Matrix games like Prisoner's Dilemma have guided research on social dile...
research
∙
03/07/2016
Learning Shared Representations in Multi-task Reinforcement Learning
We investigate a paradigm in multi-task reinforcement learning (MT-RL) i...
research
∙
06/09/2015
The Wreath Process: A totally generative model of geometric shape based on nested symmetries
We consider the problem of modelling noisy but highly symmetric shapes t...
research
∙
10/31/2014
A Comparison of learning algorithms on the Arcade Learning Environment
Reinforcement learning agents have traditionally been evaluated on small...
research
∙
12/05/2012
Compiling Relational Database Schemata into Probabilistic Graphical Models
Instead of requiring a domain expert to specify the probabilistic depend...
research
∙
07/19/2012
SiGMa: Simple Greedy Matching for Aligning Large Knowledge Bases
The Internet has enabled the creation of a growing number of large-scale...
research
∙
06/27/2012
How To Grade a Test Without Knowing the Answers --- A Bayesian Graphical Model for Adaptive Crowdsourcing and Aptitude Testing
We propose a new probabilistic graphical model that jointly models the d...
research
∙
10/21/2011
