New Learning Environment

Hello!!

I try to make my own environment and reinforcement learning algorithm to train agents starting from one initial position and reach a goal position while avoiding obstacles in a scene (and other agents).
Could someone tell me..what steps I have to follow because I am a bit confused?

1. I have to define MyArea, MyAcademy and MyAgent scripts in c-sharp?Is it right?
2. In MyAgent.cs I have to define AgentAction() function. I want to define 8 different actions of the agent, so that means he can go, east,west,south,north,southeast, northeast, southwest and northwest. How can I do this?

Thank you in advance!

 

Highly recommend you read this post and follow: https://github.com/Unity-Technologies/ml-agents/blob/master/docs/Learning-Environment-Create-New.md

Should solve all you questions.

 

Thank you for your answer!!!
I read this manual but I still have some questions!
In the function OnActionReceived() I have to define the available actions.
Something like this, is right?

switch (action)
{
case 0:
// do nothing
break;
case 1: //go right
new_pos = transform.position + new Vector3(1f, 0, 0f);
break;
case 2: //go left
new_pos = transform.position + new Vector3(-1f, 0, 0f);
break;
case 3: //go up
new_pos = transform.position + new Vector3(0f, 0, 1f);
break;
case 4: //go down
new_pos = transform.position + new Vector3(0f, 0, -1f);
break;
}

In this function, according to the action, a reward must be defined.
In my project, the rewards are distributed as follows
1.if collision between agent-obstacle == true
reward_1 = -1
else
reward_1 = 0.
2.if collision between agent-agent == true
reward_2 = -3
else
reward_2 = 0.

reward_total = reward_1 + reward_2.

Thank you in advance!!!