Questions tagged [control-problem]
For question related to the "AI control problem".
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Is overfitting always a bad thing?
DNN can be used to recognize pictures. Great. For that usage, it's better if they are somewhat flexible so as to recognize as cats even cats that are not on the pictures on which they trained (i.e. ...
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Would an AI with human intelligence have the same rights as a human under current legal frameworks?
For example, would an AI be able to own property, evict tenants, acquire debt, employ, vote, or marry? What are the legal structures in place to implement a strong AI into society?
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What's the term for death by dissolving in AI?
What's the term (if such exists) for merging with AI (e.g. via neural lace) and becoming so diluted (e.g. 1:10000) that it effectively results in a death of the original self?
It's not quite "digital ...
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What would be the best way to disable a rogue AI?
Suppose that an artificial superintelligence (ASI) has finally been developed, but it has rebelled against humanity. We can assume that the ASI is online and can reproduce itself through electronic ...
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Is there a way to protect humanity against the impending singularity?
We are careening into the future which may hold unpredictable dangers in relation to AI. I've haven't yet heard of Chappie or Robocop style police robots, but militarized drone tech is replacing many ...
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Why is GLIE Monte-Carlo control an on-policy control?
In slide 16 of his lecture 5 of the course "Reinforcement Learning", David Silver introduced GLIE Monte-Carlo Control.
But why is it an on-policy control? The sampling follows a policy $\pi$ while ...
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Could artificial intelligence cause problems for humanity after figuring out human behavior?
This BBC article suggests that intelligent algorithms, like those that select news stories and advertisements for display, could control our experience of the world and manipulate us.
Will Artificial ...
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Can the AI in a box experiment be formalized?
Introduction
The AI in a box experiment is about a super strong game AI which starts with lower resources than the opponent and the question is, if the AI is able to win the game at the end, which is ...
user11571
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Which government agencies oversee development of new AI?
Nick Bostrom talks in his book Superintelligence about the many dangers of AI. He considers it necessary that strong security mechanisms are put in place to ensure that a machine, once it gains ...
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What AI concept is behind the Mars Exploration Rover (MER)?
The Mars Exploration Rover (MER) Opportunity landed on Mars on January 25, 2004. The rover was originally designed for a 90 Sol mission (a Sol, one Martian day, is slightly longer than an Earth day at ...
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What is the Control Problem?
The Wikipedia page describes AI control problem in very intricated way.
Therefore I would like to better understand it based on some simple explanation, what's going on.
Basically I don't want any ...
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Is policy learning and online system identification the same?
In some newer robotics literature, the term system identification is used in a certain meaning. The idea is not to use a fixed model, but to create the model on the fly. So it is equal to a model-free ...
user11571
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Is learning possible without random thoughts and actions?
In my view intelligence begins once the thoughts/actions are logical rather than purely randomn based. The learning environments can be random but the logic seems to obey some elusive rules. There is ...
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Are linear approximators better suited to some tasks compared to complex neural net functions?
Model based RL attempts to learn a function $f(s_{t+1}|s_t, a_t)$ representing the environment transitions, otherwise known as a model of the system. I see linear functions are still being used in ...
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Neural networks with internal dynamics in the state-space form
Neural networks with feedback (Hopfield, Hamming, etc.) differ from ordinary neural networks (multilayer perceptrons, etc.), which turns them into a dynamic element with its own internal dynamics (if ...
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How to learn using DDPG in python solely using a timeseries datasets
I have a lengthy timeseries datasets which contains several variables (from sensors etc) to be classified as actions or states. Providing they are successfully done, I want to learn a control policy ...
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Which technologies should humanity develop before developing an AI with general superhuman intelligence?
The sequence in which new technologies are developed can be crucial for it's success and it's safe use. For example, before developing a nuclear reactor you want to have technologies like reliable ...
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Methods for sequential decision optimization problem with nonlinear bayesian reward function
I am attempting to grasp if there are any other methods out there that i am not aware of that can be beneficial given my problem context.
Being inspired from optimal experimental design communities ...
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How to Weigt Constraints in A Control Problem with Reinforcement Learning
I have a control problem for a heating device of a building with the goal to minimize the electricity costs for one day under a varying price for electricity in every hour.
(more details can be seen ...
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Using DDPG for control in multi-dimensional continuous action space?
I am relatively new to reinforcement learning, and I am trying to implement a reinforcement learning algorithm that can do continuous control in a custom environment. The state of the environment is ...
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Will robots rebel against their human creators?
There are several science fiction movies where the robots rebel against their creators: for example, the Terminator's series or I Robot.
In the future, is it possible that robots will rebel against ...
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How does reinforcement learning handle measured disturbances?
I recently encountered an interesting problem and was wondering how RL would solve it. The objective of the problem is to maximize the coffee quality, given by box X. The coffee quality objective ...
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Continuous control with DDPG: How to eliminate steady state error?
Currently I'm working on a continuous control problem using DDPG as my RL algorithm. All in all, things are working out quite well, but the algorithm does not show any tendencies to eliminate the ...
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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 ...
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Can we use a messenger that does not alter the AI to solve the control problem?
Instead of directly communicating with the AI, we would instead communicate with a messenger, who would relay our communications to the AI. The messenger would have no power to alter the AI's hardware ...
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Can future information be included in a control problem with Reinforcement Learning?
I have a control problem for a heating device of a building with the goal to minimize the electricity costs for one day under a varying price for electricity in every hour (more details can be seen ...
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How can the agent be defined in a reinforcement learning problem with a tabular dataset as the environment?
Let's assume we need to train an RL model that drops duplicates in a tabular dataset? The actions should probably defined as drop or do nothing.
But what should be the agent itself then? To me, it ...
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Using states (features) and actions from a heuristic model to estimate the value function of a reinforcement learning agent [closed]
new to RL here.
As far as i understood from RL courses, that there is two sides of reinforcement learning. Policy Evaluation, which is the task of knowing the value function for certain policy. and ...
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