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Questions tagged [topology]

Use for questions involving topology in any form in relation to Artificial Intelligence.

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13 views

Recognition and Response Generalizations for Autonomous Vehicles or Not?

It is said that the number of possible sequences of game play in the game Go is greater than the number of atoms in the universe. Whether or not that is true, imagine the number of possible sequences ...
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0answers
19 views

Semantics of natural language — is AI capable hardware and software now developed enough to realize it?

The need for semantic cognition in relation to natural language in computers is ever appearing in real problems in the field of AI. We can note a substantial increase in related posted in ...
2
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1answer
48 views

Is a calculus or ML approach to varying learning rate as a function of loss and epoch been investigated?

Many have examined the idea of modifying learning rate at discrete times during the training of an artificial network using conventional back propagation. The goals of such work have been a balance ...
5
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1answer
73 views

Neural networks of arbitrary/general topology?

Usually neural networks consist from layers, but is there research effort that tries to investigate more general topologies for connections among neurals, e.g. arbitrary directed acyclic graphs (DAGs)....
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1answer
56 views

How can AI be used to more reliably analyze and plan around the tie between climate and emissions?

Note to the Duplicate Police This question is not a duplicate of the Q&A thread referenced in the close request. The only text even remotely related in that other thread is the brief mention of ...
4
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2answers
206 views

Can neuro-evolution of augmenting topologies (NEAT) neural networks be built in TensorFlow?

I am making a machine learning program for time series data analysis and using NEAT could help the work. I started to learn TensorFlow not long ago but it seems that the computational graphs in ...
6
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0answers
54 views

Deep Networks and generalisation of Hopfield Networks

Hopfield Nets are able to store a vector and retrieve it starting from a noisy version of it. They do so setting weights in order to minimise the energy function when all neurons are set equal the ...
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2answers
260 views

Is topological sophistication necessary to the furtherance of AI?

The current machine learning trend is interpreted by some new to the disciplines of AI as meaning that MLPs, CNNs, and RNNs can exhibit human intelligence. It is true that these orthogonal structures ...
6
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2answers
110 views

In what ways is the term “topology” applied to Artificial Intelligence?

I have a 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 ...
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1answer
43 views

Will attention based networks prevail over RNN and LSTM?

There is no point in picking one of the growing number of articles that come up in a web search for, "Deep learning attention networks," however the bold claims in Attention Is All You Need, Ashish ...
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1answer
80 views

What topologies support recognition of action sequences?

The ability to recognize an object with particular identifying features from single or multiple camera shoots with the temporal dimension digitized as frames has been shown. The proof is that the ...
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0answers
27 views

Is anyone working on officiated team intelligence or anything like it?

The artificial intelligence topology that does not appear in the machine learning literature to my knowledge is that of officiated teams or round robins of them. The paradigm is a proven one in the ...
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0answers
63 views

Steps recognition

What AI concepts, topologies1, algorithms, or SaaS can be used to recognize a person eating a chocolate. For this question, image recognition draws from a real time feed, validating each of these ...
5
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1answer
240 views

What topologies are largely unexplored in machine learning?

Geometry and AI Matrices, cubes, layers, stacks, and hierarchies are what we could accurately call topologies. Consider topology in this context the higher level geometrical design of a learning ...
3
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1answer
153 views

Finding goals in Hierarchical Reinforcement Learning

In a recent paper Data-Efficient Hierarchical Reinforcement Learning, O Nachum, S Gu, H Lee, S Levine, 2018, a promising agent controlling technique called Hierarchical Reinforcement Learning was ...
7
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3answers
493 views

How are Artificial Neural Networks and the Biological Neural Networks similar and different?

I've heard multiple times that "Neural Networks are the best approximation we have to model the human brain", and I think it is commonly known that Neural Networks are modelled after our brain. I ...
0
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1answer
83 views

How to evaluate output of unlayered NN?

I used to work with 'traditional' layered neural network and I evaluated the output given certain inputs by processing layer-by-layer. With NEAT, a neural network may assume any topology and they are ...
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0answers
103 views

Number of hidden layers/neurons for Connect4 Neural Networks

I have developed a neural network program to evolve neural nets to play connect 4. I have 42 input nodes, each one corresponding to a disc on the board which can either be occupied by red (-1), empty ...
5
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1answer
78 views

Framework for Joining Multiple Modular Artificial Neural Networks

I'm looking for an industry standard framework for joining multiple neural networks in a modular way. Assume we have two or more neural networks trained to perform certain tasks. By feeding the ...
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1answer
250 views

Neuro-evolution: Is it not Supervised Learning?

If I compare back-propagation to feed-forward neuro-modulation, the latter is unsupervised in that it requires no labeled data set. Applying to it a genetic algorithm to refine topology and weights, ...
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4answers
191 views

What are some alternative information processing system beside neural network

By "neural network", I mean the typical, multilayered neural network with inputs, weights, hidden nodes and outputs, as shown in the image below: Such neural networks, in the context of evolving ...
10
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2answers
398 views

How can I plan the topology of a neural network for a given “random” problem?

Assume that I want to solve an issue with neural network that either I can't fit to already existing topologies (perceptron, Konohen, etc) or I'm simply not aware of the existence of those or I'm ...
2
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2answers
52 views

Is there a way to define the boundaries of the optimal size of a training set?

At a related question in Computer Science SE, a user told: Neural networks typically require a large training set. Is there a way to define the boundaries of the "optimal" size of a training set ...
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0answers
98 views

Number of input variables for a cellular automaton (was: Squares or hexagonal?)

A cellular automaton is a state machine which is controlled by external input. The input is given by geometrical space around a cell. In a square matrix, each automaton gets input from 4 surrounding ...