Outline one problem that may lead to printed text characters not being detected correctly.

Explain how the application uses a neural network to suggest suitable words.

Explain how ANN pattern recognition techniques are applied to ensure that the handwritten letter X in Figure 3 is recognized as a letter X.

Describe the difference between a genetic algorithm and a neural network.

Explain why the machine learning capabilities of A Doll Called Alicia may lead to instances when the child and the doll cannot communicate effectively.

Outline the basic steps involved in supervized learning algorithms.

Discuss the appropriateness of using genetic algorithms to compare the processed images with those stored in the knowledge base.

Identify two ways in which the neural network could be modified that may improve its performance.

Describe the difference between supervised learning and unsupervised learning.

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.

Explain why supervised learning may be preferred to unsupervised learning for training these networks to make predictions on the progress of this parasitic disease.

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.

Outline two advantages of developing NPCs using genetic algorithms.

Describe an appropriate set of data that could be used to train the network.

Explain the way in which the output from neuron D will be determined.

Explain how supervised learning of a genetic algorithm could be used to support the way NPCs learn.

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.

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.

Identify two features that would be required by the ANN to predict the next word in the sentence.

Outline two potential problems with training the ANN to suggest appropriate words.

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.

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.

Describe the way an NPC in a game could adapt its behaviour when moving and interacting with its environment.

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.

Outline why an ANN can be used to overcome the challenges outlined in this scenario.