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Are you ready to think about talkingconversation? You and your team are creating a specific conversation agent in for a limited specific domain . A conversation that fulfills your agent’s purposes is thus also limited. In these conversations, there are particular patterns and expectations that we can model in codeand task. The structure of such a conversation consists of sequences of dialogue moves that accomplish certain conversational and domain-specific aims that users will have - which we call conversation patterns after Moore (2019). In this section, we you will build these patterns in Prolog in the patterns.pl file. We You will also create agent responses to fill into , so the agent will be able to perform these patterns. The A conversation is between a user and an agent. The user side of the conversation is matched with intents in Dialogflow so make sure you talk to that teaminterpretation of what a user says in a conversation is done by a Dialogflow agent which tries to classify user utterances as an intent. These intents are implemented by your team members that work on Dialogflow and Filter Functions Section, so make sure to check out what they are doing and talk to them! The agent side will be created by your team in the responses.pl in file by means of text/3 2rules. Naming It is very important , it all has to match so the code can work. Let’s that the labels ('names') that you and your other team members use match, otherwise the code won’t work.
Now, let’s get started! Please read and follow the instruction on the following page:
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