General Reinforcement Learning
35 papers with code • 6 benchmarks • 7 datasets
Benchmarks
These leaderboards are used to track progress in General Reinforcement Learning
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Libraries
Use these libraries to find General Reinforcement Learning models and implementations
ProcGen
Obstacle Tower
WLD
PackIt
Avalon
bipedal-skills
POPGym
Most implemented papers
Dynamic Algorithm Configuration: Foundation of a New Meta-Algorithmic Framework
The performance of many algorithms in the fields of hard combinatorial problem solving, machine learning or AI in general depends on parameter tuning.
Counterfactual Data Augmentation using Locally Factored Dynamics
Many dynamic processes, including common scenarios in robotic control and reinforcement learning (RL), involve a set of interacting subprocesses.
Data-Efficient Reinforcement Learning with Self-Predictive Representations
We further improve performance by adding data augmentation to the future prediction loss, which forces the agent's representations to be consistent across multiple views of an observation.
Developmental Reinforcement Learning of Control Policy of a Quadcopter UAV with Thrust Vectoring Rotors
The results show faster learning with the presented approach as opposed to learning the control policy from scratch for this new UAV design created by modifications in a conventional quadcopter, i. e., the addition of more degrees of freedom (4-actuators in conventional quadcopter to 8-actuators in tilt-rotor quadcopter).
Align-RUDDER: Learning From Few Demonstrations by Reward Redistribution
For such complex tasks, the recently proposed RUDDER uses reward redistribution to leverage steps in the Q-function that are associated with accomplishing sub-tasks.
Learning to Represent Action Values as a Hypergraph on the Action Vertices
atavakol/action-hypergraph-networks
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ICLR 2021
To test this, we set forth the action hypergraph networks framework -- a class of functions for learning action representations in multi-dimensional discrete action spaces with a structural inductive bias.
Interactive Learning from Activity Description
khanhptnk/iliad
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We present a novel interactive learning protocol that enables training request-fulfilling agents by verbally describing their activities.
QKSA: Quantum Knowledge Seeking Agent
In this article we present the motivation and the core thesis towards the implementation of a Quantum Knowledge Seeking Agent (QKSA).
Catastrophic Interference in Reinforcement Learning: A Solution Based on Context Division and Knowledge Distillation
sweety-dm/interference-aware-deep-q-learning
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In this paper, we present IQ, i. e., interference-aware deep Q-learning, to mitigate catastrophic interference in single-task deep reinforcement learning.
Intelligent Trading Systems: A Sentiment-Aware Reinforcement Learning Approach
The feasibility of making profitable trades on a single asset on stock exchanges based on patterns identification has long attracted researchers.
