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Aprendizado por reforço baseado em currículo para ambiente multi-agente…
Aprendizado por reforço baseado em currículo para ambiente multi-agente com recompensas esparsas
Aprendizado por currículo
Curriculum Learning for Reinforcement Learning Domains: A Framework and Survey (2020)
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Y. Bengio, J. Louradour, R. Collobert, and J. Weston, “Curriculum learning,” (2009)
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Deep Reinforcement Learning Applied to IEEE Very Small Size Soccer Strategy (2020)
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StarCraft Micromanagement With Reinforcement Learning and Curriculum Transfer Learning (2018)
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Reverse Curriculum Generation for Reinforcement Learning (2017)
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Automated Curriculum Learning for Neural Networks (2017)
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Learning Curriculum Policies for Reinforcement Learning (2018)
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Teacher-Student Curriculum Learning (2017)
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PAIRED: A New Multi-agent Approach for Adversarial Environment Generation (2020)
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Curriculum-Based Deep Reinforcement Learning for Adaptive Robotics: A Mini-Review (2021)
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Cooperative Multi-agent Control Using Deep Reinforcement Learning (2017)
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From Few to More: Large-scale Dynamic Multiagent Curriculum Learning (2019)
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Hindsight Experience Replay (2017)
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Sparse rewards
Transfer Learning for Reinforcement Learning Domains: A Survey (2009)
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Multi-agente
Multi-Agent Reinforcement Learning for Strategic Decision Making and Control in Robotic Soccer through Self-Play (2020) (Bruno)
Emergent Social Learning via Multi-agent Reinforcement Learning
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Emergent Tool Use From Multi-Agent Autocurricula (2019)
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Emergent Complexity via Multi-Agent Competition (2017)
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Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments
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Decentralized Reinforcement Learning of Robot Behaviors (2017)
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Emergent Coordination Through Competition (2019)
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Coevolution of A Backgammon Player (1996)
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A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play (2018)
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Mastering the game of Go without human knowledge (2017)
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Grandmaster level in StarCraft II using multi-agent reinforcement learning (2019)
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Coach-Player Multi-Agent Reinforcement Learning for Dynamic Team Composition (2021)
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Dota 2 with Large Scale Deep Reinforcement Learning (2019)
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A Survey on Transfer Learning for Multiagent Reinforcement Learning Systems (2019)
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Believe What You See: Implicit Constraint Approach for Offline Multi-Agent Reinforcement Learning (2021)
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Autocurricula and the Emergence of Innovation from Social Interaction: A Manifesto for Multi-Agent Intelligence Research (2019)
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Rocket League
An Exploration of Reinforcement Learning Through Rocket League (2021) (Undergraduate Thesis)
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On the Potential of Rocket League for Driving Team AI Development (2020)
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Reinforcement Learning for Physics-Based Competitive Games (2020)
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Team Behavior of Artificial Intelligence Bots in Games (2020)
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A Behavioral Pattern Mining Approach to Model Player Skills in Rocket League (2020)
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Aprendizado por Reforço
Emergence of Locomotion Behaviours in Rich Environments (2017)
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A reinforcement learning approach to score goals in RoboCup 3D soccer simulation for nao humanoid robot (2017)
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Learning Dexterous In-Hand Manipulation (2018)
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Procedural Generalization by Planning with Self-Supervised World Models (2021)
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Dota 2 with Large Scale Deep Reinforcement Learning (2019)
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Reinforcement Learning: An Introduction (2018)
Escala
Language models are few-shot learners (2020)