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Before beginning your project we would like you all to familiarize yourself with some background knowledge about Git and Dialogflow, which are needed to successfully complete your project. These tools are Git and Dialogflow.
Everything we think you need to know can be found here: 2023: Getting Started: What to Know About Git and DialogFlow
To test your knowledge of these subjects there are two Canvas quizzes on the subjects that must be completed.
Additionally, on the page 2023: Getting Started: The Tools Used we explain and help you set up the tools infrastructure needed to complete this project.
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In this project, you will develop a cooking assistant that conversationally assists a user in selecting to select a recipe based on a variety of filters, whereas the instruction of the recipe itself is not in the scope of the Project MAS course. We chose to focus on the recipe selection activity of cooking support, since several challenging elements of building a conversational agent come together in this segment. First, there are many different ways in which this conversation may conducted, with different aspects of recipes that may be specified by the user to come to a selection (type of ingredients, cooking duration, course, etc.), and the option to mention multiple of those elements in one utterance. Second, the agent has to cover a broad knowledge space to understand what the user is looking for. Third, the agent has to reason over its database of recipes to filter for recipes that fits fit the user’s preferences.
You are provided with a prolog knowledge base of close to 1,000 recipes and their components, that still requires an effort of your group to make it usable by the cooking assistant. In the instructions we give you we walk you through how to fill in the blanksthe procedure by pinpointing aspects of the agent that need to be altered or filled in. If you fill in the these blanks the agent should work… work, but it will be pretty basic…
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But what would be really cool (and earn you more than a passing grade) is The project does not stop there. We challenge you to extend this basic bot with your own flare and ideas, so as to earn a higher grade. Read a bit more about this in our Extensions section at the end of your project.
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Note for later: When the bots start it needs to be given an initial agenda or list of pattern steps to go through. This list of patterns should be inserted on line 26 in dialog_init.mod2g. The list should be as follows: the greeting pattern, the selection pattern and then the farewell or closing pattern. |
After you finish and extend your bot you get During development and after finishing the agent, it is essential to do some testing! I mean if you bother to code it you should probably make sure it works… You will also have the privilege of This will also involve having another team conversing with your agent, and checking out another team’s bot. But that's a later problem(after your bot is done circa Week 3) that you agent yourself. You can read about this in our Testing System testing and EvaluationUser study section.
After all of that, we have blessed you with the privilege of writing a report about the experience. If you paid attention while working through the instructions and in class, it should really be nice and easyApart from a working and tested agent, your project work will result in an end report in which you describe its different features and its performance according to the testing, among others. More information on that can be found in the 2023: End Report Section.
For now, let’s get started with the fun stuff: by dividing up work among teammates.
Team Forming and Initial Set Up
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The bot is made up of parts in Eclipse and Dialogflow which you need to help finish. The goal of this project is to use Dialogflow, MARBEL, and Prolog to provide a conversational agent with the knowledge to assist us in a certain task. In this case, we have a large recipe database(recipe_database.pl) and we really need some help choosing what to eat. We should be able to tell the agent certain criteria and it should provide us with a fitting recipe. As mentioned your team will be split into pairs. The sections of work are described a briefly below so you can try and figure out who wants to do what. Make sure you also read the Evaluating Your Bot System testing page as you should be continuously testing your bot once it is minimally functioning.
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