Most Popular
1500 questions
8
votes
1 answer
Any interesting ways to combine Monte Carlo tree search with the minimax algorithm?
I've been working on a game-playing engine for about half a year now, and it uses the well known algorithms. These include minimax with alpha-beta pruning, iterative deepening, transposition tables, etc.
I'm now looking for a way to include Monte…
Inertial Ignorance
- 511
- 3
- 14
8
votes
1 answer
Which problems in AI are not machine learning?
Which problems in AI are not machine learning? Which problems involve both AI and machine learning?
Adil Mustafa
- 163
- 1
- 4
8
votes
2 answers
How to create a good fitness function?
In genetic algorithms, a function called "fitness" (or "evaluation") function is used to determine the "fitness" of the chromosomes. Creating a good fitness function is one of the challenging tasks in genetic algorithms. How would you create a good…
Abbas Ali
- 566
- 3
- 10
- 17
8
votes
3 answers
Do GANs come under supervised learning or unsupervised learning?
Do GANs come under supervised learning or unsupervised learning?
My guess is that they come under supervised learning, as we have labeled dataset of images, but I am not sure as there might be other aspects in GANs which might come into play in the…
codecracker
- 107
- 1
- 8
8
votes
1 answer
Which algorithm is used in the robot Sophia to understand and answers the questions?
Which algorithm is used in the robot Sophia to understand and answer the questions?
dua fatima
- 323
- 1
- 3
- 10
8
votes
0 answers
What are the current trends/open questions in logics for knowledge representation?
What are the future prospects in near future from a theoretical investigation of description logics, and modal logics in the context of artificial intelligence research?
mfioah
- 81
- 1
8
votes
4 answers
What are some examples of Statistical AI applications?
I believe that statistical AI uses inductive thought processes. For example, deducing a trend from a pattern, after training.
What are some examples of successfully applied Statistical AI to real-world problems?
WilliamKF
- 2,513
- 1
- 25
- 31
8
votes
1 answer
Is Experience Replay like dreaming?
Drawing parallels between Machine Learning techniques and a human brain is a dangerous operation. When it is done successfully, it can be a powerful tool for vulgarisation, but when it is done with no precaution, it can lead to major…
16Aghnar
- 601
- 3
- 11
8
votes
0 answers
Is there a difference in the architecture of deep reinforcement learning when multiple actions are performed instead of a single action?
I've built a deep deterministic policy gradient reinforcement learning agent to be able to handle any games/tasks that have only one action. However, the agent seems to fail horribly when there are two or more actions. I tried to look online for…
Rui Nian
- 433
- 3
- 13
8
votes
3 answers
What is the difference between hypothesis space and representational capacity?
I am reading Goodfellow et al Deeplearning Book. I found it difficult to understand the difference between the definition of the hypothesis space and representation capacity of a model.
In Chapter 5, it is written about hypothesis space:
One way…
Qwarzix
- 83
- 1
- 4
8
votes
3 answers
What kinds of problems can AI solve without using a deep neural network?
A lot of questions on this site seem to be asking "can I use X to solve Y?", where X is usually a deep neural network, and Y is often something already addressed by other areas of AI that are less well known?
I have some ideas about this, but am…
John Doucette
- 9,257
- 1
- 17
- 52
8
votes
2 answers
Can machine learning be used to pass the Turing test?
Can we say that the Turing test aims to develop machines or methods to reach human-level performance in all cognitive tasks and that machine learning is one of these methods that can pass the Turing test?
steve
- 81
- 1
8
votes
4 answers
How do you program fear into a neural network?
If you've been attacked by a spider once, chances are you'll never go near a spider again.
In a neural network model, having a bad experience with a spider will slightly decrease the probability you will go near a spider depending on the learning…
zooby
- 2,206
- 1
- 13
- 22
8
votes
2 answers
In what ways is the term "topology" applied to Artificial Intelligence?
I have only a general understanding of General Topology, and want to understand the scope of the term "topology" in relation to the field of Artificial Intelligence.
In what ways are topological structure and analysis applied in Artificial…
DukeZhou
- 6,227
- 5
- 25
- 53
8
votes
1 answer
How can a neural network approximate all functions when the weights are not allowed to grow exponentially?
It has been proven in the paper "Approximation by Superpositions of a Sigmoidal Function" (by Cybenko, in 1989) that neural networks are universal function approximators. I have a related question.
Assume the neural network's input and output…
Yan King Yin
- 245
- 1
- 9