We have taken you by the hand thus far and walked you through the code you were asked to produce step-by-step. But We will still be providing useful information for you to learn more about developing conversational agents, but now we will change gears a bit and leave more for you to figure out yourself, too. Remember that you can find useful information and links on the Project Background Knowledge page.

Dialogflow

Conversational patterns set expectations about what actors participating in a conversation will do, but users often will not quite meet these expectations and make moves that do not fit into the active pattern. The conversational agent will need to be able to handle such “unexpected” moves from users. “Unexpected” here means that these moves do not fit into the currently active conversational pattern, not that such moves should not be expected from users. Add . Two intents that we should actually expect to match with what a user could say are an appreciation intent and an intent for checking what the agent is capable of. You should add the following intents , following the same procedure as you did for the ‘greeting’ intent. Use the intent names as to your Dialogflow agent, making sure that you use the intent labels specified below:

1. appreciation

   If a user expresses

   Add an appreciation intent to match user expressions of appreciation or gratitude. The intent should, for example,

   ‘thanks’

   match with a “thank you” phrase.

2. Add a checkCapability

   the

   intent that

   represents

   enables a user

   querying

   to inquire about what your agent can do.

   An example phrase would be

   The intent should, for example, match with a phrase such as “What can you do?”.

Fallback intent

Another “unexpected” intent does not have its origin with the user, but rather is a result of misunderstandings that arise due to speech recognition problems. If, in our case, Dialogflow is not able to transcribe what a user says and classify it as a known intent (one of the intents created for your Dialogflow agent), it will classify what the user says as a default fallback intent. Or, in other words, the default fallback intent is matched when your agent does not recognize an end-user expression. Check out https://cloud.google.com/dialogflow/es/docs/intents-default#fallback. You do not need to add a fallback intent, as it is already available when you create your Dialogflow agent.

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Throughout the project, you should keep checking the validation page for issues and update the fallback intent by adding negative examples when they come to mind (e.g., when you add more training phrases for other intents).

Prolog and Patterns

B Patterns for Repair and Conversation Enrichment

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In responses.pl find text(describeCapability, ""). and fill in the atom with an appropriate response.

Visuals

Nothing we ask you to do here for this capability. It’s up to you.

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