3
votes
Accepted
Can I use Alpha-Beta Pruning for real life game simulation?
It also depends on the type of game.
The problem with Go is that a board that looks really good can turn into a disaster on the next move.
Games that have easy evaluations and experience only small ...
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3
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To what extent can artificially intelligent agents reliably predict trends in financial markets?
This is a highly relevant question as market trends have become more emphasized over the fundamentals of individual companies, and algorithmic trading has proven to be quite effective, particularly in ...
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2
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Accepted
What type of neural network would be most feasible for playing a realtime game?
I recommend you read up on reinforcement learning. Seeing how AirHockey is similar to the old Atari game Pong, here is a write-up (with code) about how to implement a simple neural network, that plays ...
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To what extent can artificially intelligent agents reliably predict trends in financial markets?
A couple of thoughts:
Humans can't reliably predict trends in the stock market, so expecting AI's to do so is probably unreasonable.
The above would be more true if it were proven that the movement ...
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Reinforcement Learning with asynchronous feedback
I have been looking for a while into pretty much precisely the problem you describe (including the same application domain), but haven't been able to find much.
The most obvious, mathematically "...
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2
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Accepted
Can ConvNets be used for real-time object recognition from video feed?
We are getting there, with as usual some trade-off between quality and speed.
For example Lecture 8: Spatial Localization and Detection lecture shows some benchmarks (mAP = Mean Average Precision, ...
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Where to start with reinforced learning on actions and rewards sampled from slow ongoing real life system
First you'd need to mathematically model your real environment. Probably use some differential equations.
Once you have a good model, you still won't have your real case parameters. So I can see 2 ...
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Is reinforcement learning suited for real-time systems?
Short answer: Yes, it is.
Explanation
Reinforcement learning can be considered as a online learning. That is, you can train your model with a single data/reward pairs. As with any online learning ...
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To what extent can artificially intelligent agents reliably predict trends in financial markets?
There is quite some research done by Hans-Georg Zimmermann, who has programmed Neural Networks for Siemens since some 20 years in order to predict Stock markets. He wrote some books on it, too, though ...
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What type of neural network would be most feasible for playing a realtime game?
I also recommend you take a look at the following work by Uber AI Labs who used an interesting approach to computer games:
https://eng.uber.com/deep-neuroevolution/
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Different useful approaches of implementing real-time AI?
About 15 years ago, John Laird's group at Michigan used the Soar rule-based architecture to play several FPS games effectively (Quake II, Descent III):
http://ai.eecs.umich.edu/people/laird/...
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How do autonomous robotic vacuum cleaners perceive the environment for navigation?
An agent perceives the environment through sensors and act according to the incoming percepts (agent's perceptual input at any instant). An autonomous vacuum cleaner can be as simple as
(blocki, ...
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Accepted
Which techniques can achieve neural doodle in real-time?
Most of the algorithms (based on image synthesis and style transfer, e.g. neural-doodle) haven't been proven to be highly effective in terms of real-time image processing.
However the following ...
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