All Questions

0
votes
0answers
3 views

Solvers for factored MDPs represented as RDDL or PPDDL?

I am currently investigating how we can implement probabilistic planning on our robot. Until now we are solely dealing with a deterministic, fully observable domain that we represent in PDDL (Planning ...
0
votes
0answers
4 views

Can't get the right shape for tf.squared_difference

My train data has a shape X_train.shape is (111453, 400, 5) and Y_train.shape is (111453,1) I have 3 layers and the output layer ...
0
votes
0answers
7 views

Best way to create an image dataset for CNN

I am creating a dataset made of many images which are created by preprocessing a long time series. Each image is an array of (128,128) and the there are four classes. I would like to build a dataset ...
1
vote
0answers
9 views

Putting constraints on output of deep neural network

I am training a deep neural network. There is a constraint on an output value of the network. (e.g. Output has to be between 0 and 180) I think some possible solutions are using sigmoid,tanh ...
0
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0answers
11 views

How to train a model by accounting for boundary constraints?

I've a robot traverse through a grid layout. Based on the wheel speed difference I classify actions as either straight, left or right. I computed the distances based on the time duration and the speed ...
1
vote
1answer
16 views

How much extra information can we conclude from a neural network output values?

Consider I have a 3 layers neural network. Input Layer containing 784 neurons. Hidden layer containing 100 neurons. Output layer containing 10 neurons. My objective is to make an OCR and I used ...
-2
votes
0answers
17 views

Practical usage of face embedding for face recognition tasks

I have a Facenet-like model that has been trained on faces of different identities and allows to build embedding of input faces. The training set includes N identities, $[I_1, I_2 ... I_N]$. I want ...
0
votes
1answer
19 views

Tensorflow - finding the right model on my use case

I can do this use case using purely java, levenshtein algorithm and some ratio and proportion, but my instructor wants to implement it as tensorflow, but I am having a hard time figuring out what to ...
-1
votes
0answers
8 views

Which pretrained embeddings version to choose ?

I want to use pretrained embeddings. Let's say FastText. But from the website, there is several versions available : Pre-trained word vectors learned on different sources can be downloaded below: ...
-1
votes
0answers
9 views

Machine learning for presser sensor via Accord.Net

0 down vote favorite Our system has 4 pressure sensors and they give us data each 10 seconds and we use it to claculate average presser in the sistem. So basically we have table like Timestamp - ...
3
votes
1answer
66 views

Why are Neural Networks considered Artificially Intelligent?

Why in every aspect are we now considering Neural Networks as an Artificially Intelligent entity/program?
0
votes
0answers
8 views

Usefulness of Data augmentation for non-overfitting network [NLP]

(Maybe related : Usefulness of Dropout for non-overfitting network) My neural network does not overfit. Using Data augmentation in a non-overfitting network can increase its accuracy ? Note : I'm ...
1
vote
0answers
15 views

Detect root cause across many event occurrences

Suppose there are sensors which supply numerical metrics. If a metric goes above or below healthy threshold, an event (alert) is raised. Metrics depend on each other in one way or another (we can ...
-1
votes
0answers
12 views

Data augmentation with ImageDataGenerator in Keras - Python

I have tried to use imageDataGenerator for data augmentation for following cnn wich i need to train for 5 different image classes. When i run this code, following error occurred. "Traceback (most ...
1
vote
3answers
30 views

Batch mode vs mini-batch mode vs stochastic mode

Batch size is a term used in machine learning and refers to the number of training examples utilised in one iteration. The batch size can be one of three options: batch mode: where the ...
1
vote
1answer
15 views

Representation of real numbers in Genetic Algorithm

Take a look at section 2.2.2 of this book (from Page-15 to 16). 2.2.2 Representation and Evaluation $$max f (x)= x sin(10πx)+2.0 ... ... ... (2.8)$$ $$s.t. −1 ≤ x ≤ 2$$ We can use a ...
1
vote
1answer
34 views

Reinforcement Learning (RL) how to obtain $p(s',r|s,a)$

I am trying to study the book Reinforcement Learning: An Introduction (Sutton & Barto, 2018). In chapter 3.1 the authors state the following exercise Exercise 3.5 Give a table analogous to that ...
1
vote
0answers
10 views

How exactly is equivariance achieved in capsule networks?

I have read quite a lot about capsule networks but cannot understand how the squashed vector would also rotate in response to rotation or translation of the image.A simple example would be helpful.I ...
1
vote
0answers
10 views

Variable sized input-Multi Label Classification with Neural Network

I have a data input vector ( No Image classification) which size varys from 2 to 7 entrys. Every one of them belongs to a class Out of 7. So I have a variable Input size and a variable Output size. ...
1
vote
1answer
13 views

What are the current trends/open questions in logics for knowledge representation?

What can we expect in the near future from a theoretical investigation of description logics or modal logics in the context of artificial intelligence research?
1
vote
2answers
40 views

Learning Genetic algorithm for beginners

What is the best and easiest programming language to learn to implement Genetic algorithms? C++ or Python or any other?
2
votes
1answer
22 views

Does overfitting imply an upper bound on model size/complexity?

Suppose that I have a model M that overfits a large dataset S such that the test error is 30%. Does that mean that there will always exist a model that is smaller and less complex than M that will ...
0
votes
0answers
21 views

Can AI friendliness be a goal with seminal effect?

Question Word Definitions from Merriam-Webster.com ...
0
votes
0answers
8 views

Creating a Parkour agent using Deep Reinforcement Learning

How do I go about creating a Parkour agent which uses Deep RL. I have considered one approach wherein I can learn complex maneuvers using Imitation Learning (something like DeepMimic or GAIL paper). ...
0
votes
0answers
15 views

Smart, energy efficient refrigerator design?

Opportunities For Creative Minds Do any members of this AI StackExchange have any new and creative design ideas about how to use existing AI technology to make any of the below refrigerator features ...
0
votes
0answers
18 views

Problem installing autokeras and elephas using Anaconda and pip

I am trying to install autokeras and elephas using Anaconda and pip, so that it can be used in a Jupyter notebook. However, using simply pip install autokeras ...
1
vote
0answers
23 views

First perceptron learning algorithm

I struggle to find Rosenblatts perceptron training algorithm in any of his publications from 1967 - 1951, namely: [1] Principles of Neurodynamics: Perceptrons and the Theory of Brain Mechanisms [2] ...
1
vote
0answers
7 views

To what level of abstraction must fully automated vehicles build their driving model before safety can be maximized?

There are several levels of abstraction involved in piloting and driving. Signals representing the state of the vehicle and its environment originating from multiple transducers1 Latched sample ...
1
vote
1answer
24 views

Some RL algorithms (especially policy gradients) initialize with random policies, which often manifests as random jitter on spot for a long time?

I am reviewing a statement on the website for ES regarding structured exploration. https://blog.openai.com/evolution-strategies/ Structured exploration. Some RL algorithms (especially policy ...
1
vote
3answers
37 views

When are weights updated? (feed-forward neural network)

When am I supposed to update my weights? After each forward-, and backpropagation; and or after each completed batch? Furthermore, if I am supposed to update the weights both after each forward-, and ...
1
vote
2answers
27 views

The possibility of emerging of the psychology of an artificial intelligence

The question, in short, is: what the possibility of emerging of the new branch of the psychology - the psychology of an artificial intelligence? Possibly as a new branch of an engineering psychology, ...
1
vote
0answers
11 views

How do I use truth tables to prove Entailment?

For example, consider an agent concerned with predicting the weather, with variable R indicating whether or not it is likely to rain, variable C indicating whether or not it is cloudy, and variable L ...
1
vote
1answer
11 views

AI that maximizes the storage of rectangular parallelepipeds in a bigger parallelepiped

As you can see in the title, I'm trying to program an AI in Java that would help someone optimize his storage. The user has to enter the size of his storage space (a box, a room, a warehouse etc...) ...
1
vote
1answer
23 views

How to perform neural network with output constraint?

Imagine a "simple" feedforward, fully connected neural network, with some input size, some number of hidden layers, and some # of neurons....etc BUT with a fixed number of output size (that is saying, ...
-1
votes
1answer
23 views

model.predict in Keras, Python error

I trained a model in Keras with input dimension 15 and output dimension 1. Then I tried to predict the output for a single input np.array, which I chose to be a toy example np.arange(15). However, the ...
1
vote
1answer
50 views

Reward-related formulation in reinforcement learning

I am referring to eq. 3.6 (p/g 49) based on Sutton's online book and can be found in an image below. I could not make sense of the final derivation of the equation $r(s, a, s')$. My question is ...
1
vote
1answer
19 views

Usefulness of Dropout for non-overfitting network

My neural network is simple enough and does not overfit. Dropout is a regularization technique for reducing overfitting in neural networks From Wikipedia Adding Dropout in a non-overfitting ...
1
vote
0answers
11 views

input annotations quality check for large scale image data

while dealing with image data at very large scale, there are different sources where data is coming from. Often, we do not have any control over quality of labels/ annotations. I already do use ...
1
vote
1answer
12 views

Neural Network for OMR?

I've created a neural net using the ConvNetSharp library which has 3 fully connected hidden layers. The first having 35 neurons and the other two having 25 neurons each, each layer with a ReLU layer ...
0
votes
1answer
25 views

Any problems/games/puzzles in which exhaustive search cannot show that a solution does not exist?

Introduction Exhaustive search is a method in AI planning to find a solution for so called Constraint Satisfaction Problems. (CSP). That are problems which have some conditions to fulfill and the ...
0
votes
0answers
10 views

What is the most common way \delta is defined as (in the context of a neural network)

Two highly reliable sources: Brilliant defines \delta as such: https://brilliant.org/wiki/backpropagation/ Meanwhile Nielsen defines it as such: http://neuralnetworksanddeeplearning.com/chap2.html ...
2
votes
0answers
16 views

If there are several computers on a subnet, can training time be reduced by distributing the work across them?

We have multiple computers and the ability to ssh between them. What are options using either Java, C/C++, JavaScript, or Python to distribute our learning tasks? We will be using DCNN, DQN, and LSTM ...
1
vote
1answer
24 views

When is Markov Decision Process (MDP) not adequate for goal-directed learning tasks

In the book Reinforcement Learning: An Introduction (Sutton & Barto, 2018). The authors ask Exercise 3.2: Is the MDP framework adequate to usefully represent all goal-directed learning tasks? ...
2
votes
1answer
28 views

Reinforcement Learning (RL) expected reward (Sutton & Barto, 2018)

I am new to RL and I am trying to work through the book Reinforcement Learning: An Introduction I (Sutton & Barto, 2018). In chapter 3 on Finite Markov Decision Processes, the authors write the ...
-1
votes
0answers
10 views

Classification and value prediction

Now I'm using deep learning for Human activity classification. Training data contains information like the following. acceleration, orientation, class and degree. Class is one of four activity: ...
5
votes
1answer
44 views

Does it make sense to apply softmax on top of relu?

While working through some example from Github I've found this network (it's for FashionMNIST but it doesn't really matter). Pytorch forward method (my query in upper case comments with regards to ...
1
vote
0answers
9 views

What is meant by “model discriminability for local patches within the receptive field”?

In the Abstract section of the paper Network In Network, what does the authors actually mean to say?
1
vote
0answers
15 views

How to understand marginal loglikelihood objective function as loss function (explanation of an article)?

I am reading article https://allenai.org/paper-appendix/emnlp2017-wt/ http://ai2-website.s3.amazonaws.com/publications/wikitables.pdf about training neural network and the loss function is mentioned ...
0
votes
0answers
22 views

Simple feed-forward nn does not learn

dataset can be retrieved here: https://www.kaggle.com/uciml/pima-indians-diabetes-database/downloads/diabetes.csv/1 ...
6
votes
1answer
44 views

Q-Learning the generic maze solution

After doing some exercices on Q-learning for maze solving, I wondered : my q-learning algorithms solve only ONE maze. The AI doesn't learn how to solve mazes, so how can I achieve it ? For instance ...

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