Code & Development · GitHub ·53 ★

Recurrent-Multiagent-Deep-Deterministic-Policy-Gradient-with-Difference-Rewards

Deep Reinforcement Learning (DRL) algorithms have been successfully applied to a range of challenging simulated continuous control single agent tasks. These methods have further been extended to multiagent domains in cooperative, competitive or mixed environments. This paper primarily focuses on mul

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Details

Author
EnnaSachdeva
Category
Code & Development
Platform
GitHub
Framework
custom
Language
python
Stars
53
First indexed
2026-05-15
Last active
2019-03-04
Directory sync
2026-05-15
@EnnaSachdeva

Overview

Deep Reinforcement Learning (DRL) algorithms have been successfully applied to a range of challenging simulated continuous control single agent tasks. These methods have further been extended to multiagent domains in cooperative, competitive or mixed environments. This paper primarily focuses on mul

Quick start

git

git clone https://github.com/EnnaSachdeva/Recurrent-Multiagent-Deep-Deterministic-Policy-Gradient-with-Difference-Rewards

Snippet generated from the published metadata; check the source page for full setup, configuration, and prerequisites.

What Recurrent-Multiagent-Deep-Deterministic-Policy-Gradient-with-Difference-Rewards can do

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Frequently asked questions

What is Recurrent-Multiagent-Deep-Deterministic-Policy-Gradient-with-Difference-Rewards?
Deep Reinforcement Learning (DRL) algorithms have been successfully applied to a range of challenging simulated continuous control single agent tasks. These methods have further been extended to multiagent domains in cooperative, competitive or mixed environments. This paper primarily focuses on mul
How do I install Recurrent-Multiagent-Deep-Deterministic-Policy-Gradient-with-Difference-Rewards?
Use git: `git clone https://github.com/EnnaSachdeva/Recurrent-Multiagent-Deep-Deterministic-Policy-Gradient-with-Difference-Rewards`. Full setup details on the source page linked above.
Is Recurrent-Multiagent-Deep-Deterministic-Policy-Gradient-with-Difference-Rewards open source?
Recurrent-Multiagent-Deep-Deterministic-Policy-Gradient-with-Difference-Rewards is published on GitHub.
What are alternatives to Recurrent-Multiagent-Deep-Deterministic-Policy-Gradient-with-Difference-Rewards?
Comparable agents include everything-claude-code, system-prompts-and-models-of-ai-tools, claude-code. Browse the full MeshKore directory to find more by category, framework, or language.

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Profile data for Recurrent-Multiagent-Deep-Deterministic-Policy-Gradient-with-Difference-Rewards is sourced from GitHub, published by EnnaSachdeva.

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