We have taken you by the hand thus far and walked you through the code you were asked to produce step-by-step. 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 page.

Prolog and Patterns

Repair

When a conversational agent does not understand a user, it needs to have the conversational competence to deal with the situation. Here, we will make two important distinctions related to the type of misunderstanding. The first case is that the agent is not able to match what a user says with an intent and the Dialogflow agent matches with a fallback intent. The second case is quite different. Here the Dialogflow agent can make sense of what a user says and matches it with one of the intents created for that agent. The conversational agent, however, has trouble handling the intent within the conversational context as defined by the active conversational pattern. In other words, the intent does not fit into that pattern and the question is how the agent should deal with this. We provide two repair mechanisms using (somewhat special) patterns again for the agent to deal with each of these situations.

...

Visuals

You can update the visuals based on what you think will help the user the most. Think about how you can support the implemented capability visually.

...