DeepAI AI Chat
Log In Sign Up

DIAMBRA Arena: a New Reinforcement Learning Platform for Research and Experimentation

10/19/2022
by   Alessandro Palmas, et al.
0

The recent advances in reinforcement learning have led to effective methods able to obtain above human-level performances in very complex environments. However, once solved, these environments become less valuable, and new challenges with different or more complex scenarios are needed to support research advances. This work presents DIAMBRA Arena, a new platform for reinforcement learning research and experimentation, featuring a collection of high-quality environments exposing a Python API fully compliant with OpenAI Gym standard. They are episodic tasks with discrete actions and observations composed by raw pixels plus additional numerical values, all supporting both single player and two players mode, allowing to work on standard reinforcement learning, competitive multi-agent, human-agent competition, self-play, human-in-the-loop training and imitation learning. Software capabilities are demonstrated by successfully training multiple deep reinforcement learning agents with proximal policy optimization obtaining human-like behavior. Results confirm the utility of DIAMBRA Arena as a reinforcement learning research tool, providing environments designed to study some of the most challenging topics in the field.

READ FULL TEXT

page 1

page 3

page 4

page 10

page 11

03/10/2020

Retrospective Analysis of the 2019 MineRL Competition on Sample Efficient Reinforcement Learning

To facilitate research in the direction of sample-efficient reinforcemen...
03/10/2020

The MineRL Competition on Sample-Efficient Reinforcement Learning Using Human Priors: A Retrospective

To facilitate research in the direction of sample-efficient reinforcemen...
10/07/2016

Deep Reinforcement Learning From Raw Pixels in Doom

Using current reinforcement learning methods, it has recently become pos...
06/29/2021

Multiagent Deep Reinforcement Learning: Challenges and Directions Towards Human-Like Approaches

This paper surveys the field of multiagent deep reinforcement learning. ...
09/30/2020

PettingZoo: Gym for Multi-Agent Reinforcement Learning

This paper introduces PettingZoo, a library of diverse sets of multi-age...
09/10/2018

ViZDoom Competitions: Playing Doom from Pixels

This paper presents the first two editions of Visual Doom AI Competition...
05/16/2022

A Deep Reinforcement Learning Blind AI in DareFightingICE

This paper presents a deep reinforcement learning AI that uses sound as ...