DP Computer Science Questionbank
B.4 Communication modelling and simulation
Description
[N/A]Directly related questions
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19M.2.HL.TZ0.8b:
Identify two ways in which the neural network could be modified that may improve its performance.
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19M.2.HL.TZ0.8a:
Describe the difference between a genetic algorithm and a neural network.
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19M.2.HL.TZ0.8e:
Companies such as MAGS are considering products that use unsupervised learning rather than supervised learning.
Explain the benefits of unsupervised learning in developing products such as A Doll Called Alicia.
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19M.2.HL.TZ0.8c:
Describe the difference between supervised learning and unsupervised learning.
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19M.2.HL.TZ0.8d:
Explain why the machine learning capabilities of A Doll Called Alicia may lead to instances when the child and the doll cannot communicate effectively.
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17N.2.HL.TZ0.8b:
Describe an appropriate set of data that could be used to train the network.
- 17N.2.HL.TZ0.8c.ii: State the number of neurons that would be in the output layer.
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17N.2.HL.TZ0.8d:
Explain the way in which the output from neuron D will be determined.
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17N.2.HL.TZ0.8e:
The network is set up with initial values. The outputs are compared with the desired outputs.
Identify the steps that now take place to train the network.
- 17N.2.HL.TZ0.8c.i: State the number of neurons that would be in the input layer.
- 17N.2.HL.TZ0.8a: Explain one reason why ANNs are suitable for solving the types of problems found in these areas.
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17N.2.HL.TZ0.9:
Google Translate is an algorithm whose function is to translate text from one language to another. One of the resources that it uses is the body of documents produced by the United Nations which are routinely translated by humans into various languages.
Discuss the reasons why Google Translate takes a probabilistic approach in preference to a cognitive rule-based approach.
- 18N.2.HL.TZ0.8a: Genetic algorithms follow an iterative process in developing a solution to a problem. Outline...
- 18N.2.HL.TZ0.8b.i: Outline why neural networks need to be trained before they can be used in this analysis.
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18N.2.HL.TZ0.8b.ii:
Explain why supervised learning may be preferred to unsupervised learning for training these networks to make predictions on the progress of this parasitic disease.
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18N.2.HL.TZ0.8c:
Many companies now use an automated response system when answering basic telephone queries from customers. This system uses speech analysis together with recorded messages.
Explain why the content of the messages given by these systems must be carefully chosen.
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19N.2.HL.TZ0.8a:
Outline one problem that may lead to printed text characters not being detected correctly.
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19N.2.HL.TZ0.8c:
Explain how ANN pattern recognition techniques are applied to ensure that the handwritten letter X in Figure 3 is recognized as a letter X.
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19N.2.HL.TZ0.8f:
Outline two potential problems with training the ANN to suggest appropriate words.
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19N.2.HL.TZ0.8d:
Identify two features that would be required by the ANN to predict the next word in the sentence.
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19N.2.HL.TZ0.8b:
Outline why an ANN can be used to overcome the challenges outlined in this scenario.
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19N.2.HL.TZ0.8e:
Explain how the application uses a neural network to suggest suitable words.
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20N.2.HL.TZ0.8c:
Describe the way an NPC in a game could adapt its behaviour when moving and interacting with its environment.
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20N.2.HL.TZ0.8a:
Outline two advantages of developing NPCs using genetic algorithms.
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20N.2.HL.TZ0.8d:
The last stage of NPC development is verbal communication with player characters and other NPCs. To assist with this process, it was decided to explore research related to chatbots.
Explain the benefits of giving NPCs the functionality of chatbots.
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20N.2.HL.TZ0.8b:
Explain how supervised learning of a genetic algorithm could be used to support the way NPCs learn.
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18M.2.HL.TZ0.8b:
The following block diagram illustrates a neural network used by a supervized learning algorithm to calculate a resulting value RES, for a given set of inputs.
The neural network in the block diagram contains 60 nodes in the input layer (block I), 36 nodes in the hidden layer (block H) and 6 nodes in the outermost layer (block O). The solid black arrows indicate that all nodes in one layer are feeding all nodes in the successive layer. In particular, the value RES is calculated by using all nodes in O.
Calculate the number of weights that the above neural network uses in producing a value for RES. Show the details of your calculation.
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18M.2.HL.TZ0.9b:
Discuss the appropriateness of using genetic algorithms to compare the processed images with those stored in the knowledge base.
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18M.2.HL.TZ0.8a:
Outline the basic steps involved in supervized learning algorithms.
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18M.2.HL.TZ0.10:
Machine translators are regularly used to translate text from one language to another. In spite of the advances that have been made in this field, the output may still need to be proofread by a human.
Describe two problems that these translators may encounter when translating from one language to another.