Short Overview: Authors: Sumeet Batra*, Zhehui Huang*, Aleksei Petrenko*, Tushar Kumar, Artem Molchanov, Gaurav Sukhatme - The first three ... Carlo Pinciroli, Mohamed Salaheddine Talamali, Andreagiovanni Reina, James A.

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Autonomous systems have achieved superhuman performance in isolation or simulation, yet they remain brittle in shared, ... Simulation - Decentralized Control of Quadrotor Swarms with End to end Deep Reinforcement Learning

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Designing resource-collection algorithms for relatively simple physical robots that are effective given the noise and uncertainty of ... Authors: Sumeet Batra*, Zhehui Huang*, Aleksei Petrenko*, Tushar Kumar, Artem Molchanov, Gaurav Sukhatme - The first three ... Carlo Pinciroli, Mohamed Salaheddine Talamali, Andreagiovanni Reina, James A.

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  • Authors: Sumeet Batra*, Zhehui Huang*, Aleksei Petrenko*, Tushar Kumar, Artem Molchanov, Gaurav Sukhatme - The first three ...
  • Simulation - Decentralized Control of Quadrotor Swarms with End to end Deep Reinforcement Learning
  • Designing resource-collection algorithms for relatively simple physical robots that are effective given the noise and uncertainty of ...
  • Autonomous systems have achieved superhuman performance in isolation or simulation, yet they remain brittle in shared, ...
  • Carlo Pinciroli, Mohamed Salaheddine Talamali, Andreagiovanni Reina, James A.

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Visual Context Gallery

Foraging Swarms using Multi-Agent Reinforcement Learning
Decentralized Control of Quadrotor Swarms with End to end Deep Reinforcement Learning (Simulation)
Introduction to Multi-Agent Reinforcement Learning
Superhuman Safe and Agile Racing through Multi-Agent Reinforcement Learning
Learning Cooperative Strategies for Drone Swarms Using Multi-Agent Reinforcement Learning
Kilobot foraging: Comparison between ARGoS simulation and reality
Comparing Physical and Simulated  Robot Swarms Using DDSA and CPFA Foraging Strategies
Multi-Agent Hide and Seek
AI Olympics (multi-agent reinforcement learning)
Simulation - Decentralized Control of Quadrotor Swarms with End to end Deep Reinforcement Learning
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See Reader Notes
Foraging Swarms using Multi-Agent Reinforcement Learning

Foraging Swarms using Multi-Agent Reinforcement Learning

Read more details and related context about Foraging Swarms using Multi-Agent Reinforcement Learning.

Decentralized Control of Quadrotor Swarms with End to end Deep Reinforcement Learning (Simulation)

Decentralized Control of Quadrotor Swarms with End to end Deep Reinforcement Learning (Simulation)

Authors: Sumeet Batra*, Zhehui Huang*, Aleksei Petrenko*, Tushar Kumar, Artem Molchanov, Gaurav Sukhatme - The first three ...

Introduction to Multi-Agent Reinforcement Learning

Introduction to Multi-Agent Reinforcement Learning

Read more details and related context about Introduction to Multi-Agent Reinforcement Learning.

Superhuman Safe and Agile Racing through Multi-Agent Reinforcement Learning

Superhuman Safe and Agile Racing through Multi-Agent Reinforcement Learning

Autonomous systems have achieved superhuman performance in isolation or simulation, yet they remain brittle in shared, ...

Learning Cooperative Strategies for Drone Swarms Using Multi-Agent Reinforcement Learning

Learning Cooperative Strategies for Drone Swarms Using Multi-Agent Reinforcement Learning

Companion video to "Learning Cooperative Strategies for Drone

Kilobot foraging: Comparison between ARGoS simulation and reality

Kilobot foraging: Comparison between ARGoS simulation and reality

Carlo Pinciroli, Mohamed Salaheddine Talamali, Andreagiovanni Reina, James A. R. Marshall, Vito Trianni. Simulating Kilobots ...

Comparing Physical and Simulated  Robot Swarms Using DDSA and CPFA Foraging Strategies

Comparing Physical and Simulated Robot Swarms Using DDSA and CPFA Foraging Strategies

Designing resource-collection algorithms for relatively simple physical robots that are effective given the noise and uncertainty of ...

Multi-Agent Hide and Seek

Multi-Agent Hide and Seek

Read more details and related context about Multi-Agent Hide and Seek.

AI Olympics (multi-agent reinforcement learning)

AI Olympics (multi-agent reinforcement learning)

Read more details and related context about AI Olympics (multi-agent reinforcement learning).

Simulation - Decentralized Control of Quadrotor Swarms with End to end Deep Reinforcement Learning

Simulation - Decentralized Control of Quadrotor Swarms with End to end Deep Reinforcement Learning

Simulation - Decentralized Control of Quadrotor Swarms with End to end Deep Reinforcement Learning