Unity Tennis Environment using Multi-agent DDPG

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Unity Tennis Environment using Multi-agent DDPG

Date

May 12, 2019

Contributor

Ashutosh Tiwari

Categories

Deep learning, r l

Project Heads-up

The projetc uses the Tennis environment, where two agents control rackets to bounce ball over a net.
If an agent hits a ball over net, the agent receives a reward of +0.1. If an agent lets a ball hit the ground or hits the ball
out of bounds, the agent receives a reward of -0.01. Thus, the goal of each agent is to keep the ball in play.
The observation space is 24-dimensional consisting of 8 variables corresponding to the position and velocity
of the ball and racket. Each agent receives its own, local observation. Two continuous actions are available, corresponding to movement toward (or away from) the net, and jumping. The accompanying research paper can be found here.

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