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Questions tagged [control-theory]

For questions related to control theory and its relation to reinforcement learning and other artificial intelligence sub-fields.

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Control algorithms when system dynamics are stochastic and/or unknown

I'm working on a traffic signal control problem, which I am currently approaching with Reinforcement Learning, but I want to try some other control algorithms. This is hard for me because we don't ...
0 votes
0 answers

Seeking methods to incorporate arbitrary actuator faults for Control Optimization

I am working on a problem where a control method, backed by a Neural Network (NN), dictates the movement of a 1D actuator to influence a specific process. This actuator can move linearly within a set ...
23 votes
2 answers

What is the difference between reinforcement learning and optimal control?

Coming from a process (optimal) control background, I have begun studying the field of deep reinforcement learning. Sutton & Barto (2015) state that particularly important (to the writing of the ...
2 votes
0 answers

How do self-driving cars perform lane changes?

I am a bit stuck trying to understand how a lane change is performed from an operational point of view. Let's assume a self-driving car uses an occupancy grid map for local planning, this map may even ...
4 votes
1 answer

Are there examples of neural networks (used for control) implemented on a FPGA or on a neurochip?

Greetings to all respected colleagues! I want to consult on the use of FPGAs and neurochips. I plan to use it in my laboratory project for programming control systems on neural networks. In my work,...
3 votes
1 answer

What does a joint probability density function have to do with Stochastic Optimal Control and Reinforcement Learning?

I stumbled upon a job offer from a company that was looking for someone who was good with Reinforcement Learning (applied to finance) and something in their offer caught my eye. It goes something like ...
3 votes
0 answers

How to deal with approximate states when doing path planning?

If one is interested in implementing a path planning algorithm that is grid-based, one needs to consider the fact that your grid points will never represent the true state of the robot. How is this ...
4 votes
1 answer

Can OpenAI simulations be used in real world applications?

I know that classical control systems have been used to solve the problem of the inverted pendulum - inverted pendulum. But I've seen that people have also used machine learning techniques to solve ...
1 vote
0 answers

Solving the dead time problem for control using reinforcement learning

There are several occasion that reinforcement learning can be used as a control mean. The action is for example the set target temperature (which in many occasions change with time) and the state is ...
4 votes
1 answer

How do I solve this optimal control problem with reinforcement learning?

I am new to reinforcement learning. I would like to solve an optimal control problem with reinforcement learning. The objective is for a wolf to catch a rabbit. The wolf and the rabbit run on a ...
4 votes
1 answer

Is there any difference between a control and an action in reinforcement learning?

There are reinforcement learning papers (e.g. Metacontrol for Adaptive Imagination-Based Optimization) that use (apparently, interchangeably) the term control or action to refer to the effect of the ...
24 votes
1 answer

When should I use Reinforcement Learning vs PID Control?

When designing solutions to problems such as the Lunar Lander on OpenAIGym, Reinforcement Learning is a tempting means of giving the agent adequate action control so as to successfully land. But ...