Joel Z. Leibo

According to our database1, Joel Z. Leibo authored at least 52 papers between 2011 and 2020.

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Bibliography

2020
Smooth markets: A basic mechanism for organizing gradient-based learners.
CoRR, 2020

Bounds and dynamics for empirical game theoretic analysis.
Auton. Agents Multi Agent Syst., 2020

Smooth markets: A basic mechanism for organizing gradient-based learners.
Proceedings of the 8th International Conference on Learning Representations, 2020

Social Diversity and Social Preferences in Mixed-Motive Reinforcement Learning.
Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

Silly Rules Improve the Capacity of Agents to Learn Stable Enforcement and Compliance Behaviors.
Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

Learning to Resolve Alliance Dilemmas in Many-Player Zero-Sum Games.
Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

2019
Toward high-performance, memory-efficient, and fast reinforcement learning - Lessons from decision neuroscience.
Sci. Robotics, 2019

Options as responses: Grounding behavioural hierarchies in multi-agent RL.
CoRR, 2019

Learning Reciprocity in Complex Sequential Social Dilemmas.
CoRR, 2019

Autocurricula and the Emergence of Innovation from Social Interaction: A Manifesto for Multi-Agent Intelligence Research.
CoRR, 2019

Generalization of Reinforcement Learners with Working and Episodic Memory.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Interval timing in deep reinforcement learning agents.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning.
Proceedings of the 36th International Conference on Machine Learning, 2019

Evolving Intrinsic Motivations for Altruistic Behavior.
Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019

Malthusian Reinforcement Learning.
Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019

The Imitation Game: Learned Reciprocity in Markov games.
Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019

2018
Intrinsic Social Motivation via Causal Influence in Multi-Agent RL.
CoRR, 2018

Human-level performance in first-person multiplayer games with population-based deep reinforcement learning.
CoRR, 2018

Unsupervised Predictive Memory in a Goal-Directed Agent.
CoRR, 2018

Inequity aversion resolves intertemporal social dilemmas.
CoRR, 2018

Kickstarting Deep Reinforcement Learning.
CoRR, 2018

Psychlab: A Psychology Laboratory for Deep Reinforcement Learning Agents.
CoRR, 2018

Inequity aversion improves cooperation in intertemporal social dilemmas.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Emergent Communication through Negotiation.
Proceedings of the 6th International Conference on Learning Representations, 2018

A Generalised Method for Empirical Game Theoretic Analysis.
Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, 2018

Value-Decomposition Networks For Cooperative Multi-Agent Learning Based On Team Reward.
Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, 2018

Deep Q-learning From Demonstrations.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Building Machines that Learn and Think for Themselves: Commentary on Lake et al., Behavioral and Brain Sciences, 2017.
CoRR, 2017

Symmetric Decomposition of Asymmetric Games.
CoRR, 2017

Value-Decomposition Networks For Cooperative Multi-Agent Learning.
CoRR, 2017

Learning from Demonstrations for Real World Reinforcement Learning.
CoRR, 2017

A multi-agent reinforcement learning model of common-pool resource appropriation.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Reinforcement Learning with Unsupervised Auxiliary Tasks.
Proceedings of the 5th International Conference on Learning Representations, 2017

Learning to reinforcement learn.
Proceedings of the 39th Annual Meeting of the Cognitive Science Society, 2017

Multi-agent Reinforcement Learning in Sequential Social Dilemmas.
Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems, 2017

2016
Unsupervised learning of invariant representations.
Theor. Comput. Sci., 2016

View-tolerant face recognition and Hebbian learning imply mirror-symmetric neural tuning to head orientation.
CoRR, 2016

Model-Free Episodic Control.
CoRR, 2016

DeepMind Lab.
CoRR, 2016

Using Fast Weights to Attend to the Recent Past.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Invariant representation for blur and down-sampling transformations.
Proceedings of the 2016 IEEE International Conference on Image Processing, 2016

How Important Is Weight Symmetry in Backpropagation?
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
The Invariance Hypothesis Implies Domain-Specific Regions in Visual Cortex.
PLoS Computational Biology, 2015

Approximate Hubel-Wiesel Modules and the Data Structures of Neural Computation.
CoRR, 2015

2014
Unsupervised learning of clutter-resistant visual representations from natural videos.
CoRR, 2014

Subtasks of Unconstrained Face Recognition.
Proceedings of the VISAPP 2014, 2014

2013
Throwing Down the Visual Intelligence Gauntlet.
Proceedings of the Machine Learning for Computer Vision, 2013

Can a biologically-plausible hierarchy effectively replace face detection, alignment, and recognition pipelines?
CoRR, 2013

Unsupervised Learning of Invariant Representations in Hierarchical Architectures.
CoRR, 2013

Learning invariant representations and applications to face verification.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

2012
Learning and disrupting invariance in visual recognition with a temporal association rule.
Frontiers Comput. Neurosci., 2012

2011
Why The Brain Separates Face Recognition From Object Recognition.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011


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