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7 votes
Accepted

What is the definition of `rollout' in neural network or OpenAI gym

The standard use of “rollout” (also called a “playout”) is in regard to an execution of a policy from the current state when there is some uncertainty about the next state or outcome - it is one ...
adamconkey's user avatar
6 votes

What is the definition of `rollout' in neural network or OpenAI gym

The definition of "rollouts" given by Planning chemical syntheses with deep neural networks and symbolic AI (Segler, Preuss & Waller ; doi: 10.1038/nature25978 ; credit to jsotola): Rollouts ...
Sun Haozhe's user avatar
3 votes

Applications of Reinforcement Learning

It's true that using RL in robotics involves many challenges, including the usually high dimensionality of problem spaces, the cost and limitations of real-world sessions, the impossibility or ...
xperroni's user avatar
  • 1,363
3 votes

PID tuning with (Deep) Reinforcement Learning

Many reainforcement learning methods require descrete actions. As you indentified, increasing and decreasing the values is one option. If it is an adaptive PID, then it might take some time to ...
50k4's user avatar
  • 6,682
3 votes
Accepted

PID tuning with (Deep) Reinforcement Learning

I read a bit more and realized that in RL states and rewards accept a wide variety of interpretations and this is the real complexity nowadays of this learning problem. In case of PID values, problem ...
galtor's user avatar
  • 470
2 votes

What are myopic and non-myopic policies?

A myopic policy is one that simply maximises the average immediate reward. It is "myopic" in the sense that it only considers the single criterion. It has the advantage of being relatively easy to ...
sempaiscuba's user avatar
  • 1,074
2 votes
Accepted

Reinforcement Learning in global and local path planning for mobile robots and self-driving car

No, this is not applicable for a car, it is just an introductory, extremely simplified example. It is one step closer to a mobile robot, then to a car, at least a mobile robot (at least some of them) ...
50k4's user avatar
  • 6,682
1 vote

what are the main steps to build a swarm robots system and train it to achieve foraging task using deep Q network

Let's assume this foraging task is a continuous motion planning problem, i.e. you have dynamics accounted for (does not necessarily have to be the case, but should help convergence if it is) and your ...
domo_arigato's user avatar
1 vote

Reinforcement Learning in global and local path planning for mobile robots and self-driving car

1- No it is not. This example is the beginning of RL, while Self-driving cars are way much complex. In a simplified view, there are two main differences. state and action in the shown example are ...
hosh0425's user avatar
1 vote

Having Issues Importing and Using RLGlue locally with Python For Reinforcement Learning

This worked for me: from RLGlue.rl_glue import RLGlue This is only with the Coursera version of RLGlue
Benny Friedman's user avatar
1 vote

Reinforcement train butterfly robot in virtual reality?

Unreal, Unity and other game engines, Gazebo, Mujoco and other Physics engines are good at simulating multi body dynamics. There is no deep conceptual difference between them. You can use whichever ...
50k4's user avatar
  • 6,682
1 vote

What type of rigid body rotation can best be learned by neural networks?

The main problem is the continuity of the representation. This paper explains it.
50k4's user avatar
  • 6,682
1 vote

What type of rigid body rotation can best be learned by neural networks?

Every three-dimensional parameterization of rotations has singularity. So even if you would implement the kinematics directly you would still run into trouble for some rotations when using Euler ...
fibonatic's user avatar
  • 941
1 vote

What are myopic and non-myopic policies?

You first have to be clear about the core RL terms, to understand myopic and non-myopic policies: Policy: Suppose each cell in the grid below is a state that the RL agent can be in. From each state, ...
quartzfun's user avatar
  • 163
1 vote

Tuning Line follower PID constants with Q-learning

I am currently working on a very similar project, the only difference is that I am using a simulation package (MATLAB Simmechanics) where I have modeled a mobile robot with 2 actuated wheels and a ...
csg's user avatar
  • 244

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