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 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. 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 to your Dialogflow agent, making sure that you use the intent labels specified below:

...

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

...

Repair

...

A good handling of repair is vital to making your agent robust to misunderstanding. There are a few common ways in which misunderstanding occurs, that need to be addressed by proper repair patterns.

b12 The agent does not understand the user's’s utterance

...

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 is able to 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.

An example of a user expression that will not be recognized by our Dialogflow agent is the following:

U: Have you read the Hobbit?

A: what What do you mean?

In this case, the agent does not understand the user's utterance (a fallback intent will be received from the Dialogflow agent). In Moore and Arar, 2019’s taxonomy, this is a b12 pattern.

Your user has just said something odd or does not match the current situation, and so your Dialogflow cannot identify the user's intention and goes to a default fallback intent. In this pattern, your agent can try to come to an understanding by asking for a rephrasing with ‘paraphraseRequest’. Add a b12 pattern using the defaultFallback intent and paraphraseRequest response.

...

When a user wants to know what your agent can do for it, i.e., check what capabilities it has, the agent should be able to provide an appropriate reply. The key challenge here is to fill in the ___ in the example below. What would be a good response to such a general request for information of a user? The capability check should give a user enough guidance to understand how to talk to the agent or, even better, ideally also to ask more specific questions about its capabilities, for example, “tell me more about the recipe features you know about” (cf. Moore and Arar, 2019).

Example:

U: What can you do?

...

In Moore and Arar’s taxonomy, this classifies as a c30 pattern for a general capability check. Implement this pattern in the patterns.pl file. You should use the intent labels checkCapability and describeCapability. Define the agent’s response in the responses.pl file.

Visuals

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

...