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OpenSpiel: A Framework for Reinforcement Learning in Games

26 Aug 2019deepmind/open_spiel

OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games.

GENERAL REINFORCEMENT LEARNING

Gibson Env: Real-World Perception for Embodied Agents

CVPR 2018 StanfordVL/GibsonEnv

Developing visual perception models for active agents and sensorimotor control are cumbersome to be done in the physical world, as existing algorithms are too slow to efficiently learn in real-time and robots are fragile and costly.

DOMAIN ADAPTATION GENERAL REINFORCEMENT LEARNING ROBOT NAVIGATION

Sample Factory: Egocentric 3D Control from Pixels at 100000 FPS with Asynchronous Reinforcement Learning

ICML 2020 alex-petrenko/sample-factory

In this work we aim to solve this problem by optimizing the efficiency and resource utilization of reinforcement learning algorithms instead of relying on distributed computation.

FPS GAMES GENERAL REINFORCEMENT LEARNING MULTI-AGENT REINFORCEMENT LEARNING

Stabilizing Transformers for Reinforcement Learning

ICML 2020 lucidrains/x-transformers

Harnessing the transformer's ability to process long time horizons of information could provide a similar performance boost in partially observable reinforcement learning (RL) domains, but the large-scale transformers used in NLP have yet to be successfully applied to the RL setting.

GENERAL REINFORCEMENT LEARNING LANGUAGE MODELLING MACHINE TRANSLATION

AIXIjs: A Software Demo for General Reinforcement Learning

22 May 2017aslanides/aixijs

The universal Bayesian agent AIXI (Hutter, 2005) is a model of a maximally intelligent agent, and plays a central role in the sub-field of general reinforcement learning (GRL).

GENERAL REINFORCEMENT LEARNING OPENAI GYM

Generalised Discount Functions applied to a Monte-Carlo AImu Implementation

3 Mar 2017aslanides/aixijs

We have added to the GRL simulation platform AIXIjs the functionality to assign an agent arbitrary discount functions, and an environment which can be used to determine the effect of discounting on an agent's policy.

GENERAL REINFORCEMENT LEARNING

Is Deep Reinforcement Learning Really Superhuman on Atari? Leveling the playing field

13 Aug 2019valeoai/rainbow-iqn-apex

In the Arcade Learning Environment (ALE), small changes in environment parameters such as stochasticity or the maximum allowed play time can lead to very different performance.

ATARI GAMES GENERAL REINFORCEMENT LEARNING

Counterfactual Data Augmentation using Locally Factored Dynamics

NeurIPS 2020 spitis/mrl

Many dynamic processes, including common scenarios in robotic control and reinforcement learning (RL), involve a set of interacting subprocesses.

DATA AUGMENTATION GENERAL REINFORCEMENT LEARNING MULTI-GOAL REINFORCEMENT LEARNING