Multi-Goal Reinforcement Learning
17 papers with code • 0 benchmarks • 2 datasets
Benchmarks
These leaderboards are used to track progress in Multi-Goal Reinforcement Learning
UniMiB SHAR
bipedal-skills
Most implemented papers
Multi-Goal Reinforcement Learning: Challenging Robotics Environments and Request for Research
DartEnv/dart-env
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The purpose of this technical report is two-fold.
Intrinsically Motivated Goal Exploration Processes with Automatic Curriculum Learning
We present an algorithmic approach called Intrinsically Motivated Goal Exploration Processes (IMGEP) to enable similar properties of autonomous learning in machines.
Maximum Entropy-Regularized Multi-Goal Reinforcement Learning
ruizhaogit/mep
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This objective encourages the agent to maximize the expected return, as well as to achieve more diverse goals.
Learning to Reach Goals via Iterated Supervised Learning
Current reinforcement learning (RL) algorithms can be brittle and difficult to use, especially when learning goal-reaching behaviors from sparse rewards.
An Inductive Bias for Distances: Neural Nets that Respect the Triangle Inequality
spitis/deepnorms
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ICLR 2020
When defining distances, the triangle inequality has proven to be a useful constraint, both theoretically--to prove convergence and optimality guarantees--and empirically--as an inductive bias.
Maximum Entropy Gain Exploration for Long Horizon Multi-goal Reinforcement Learning
spitis/mrl
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ICML 2020
What goals should a multi-goal reinforcement learning agent pursue during training in long-horizon tasks?
An Open-Source Multi-Goal Reinforcement Learning Environment for Robotic Manipulation with Pybullet
This work re-implements the OpenAI Gym multi-goal robotic manipulation environment, originally based on the commercial Mujoco engine, onto the open-source Pybullet engine.
Grounding Hindsight Instructions in Multi-Goal Reinforcement Learning for Robotics
knowledgetechnologyuhh/hipss
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We show that hindsight instructions improve the learning performance, as expected.
CURIOUS: Intrinsically Motivated Modular Multi-Goal Reinforcement Learning
In open-ended environments, autonomous learning agents must set their own goals and build their own curriculum through an intrinsically motivated exploration.
Bias-Reduced Hindsight Experience Replay with Virtual Goal Prioritization
filipolszewski/prioritized-her
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We call this property the instructiveness of the virtual goal and define it by a heuristic measure, which expresses how well the agent will be able to generalize from that virtual goal to actual goals.
