Welcome to this page with a basic overview of the required background information for this project. Some of this information you have most likely seen before in other courses, but some of it will also be new to you. We expect you to have a decent understanding of the material listed below, as it is necessary to be able to complete this project successfully. The background knowledge that we provide here is related to some of the main tools, software, and programming languages that are used within the project. There are a few quizzes that you need to complete, where the material presented below can be used to prepare (see also Course Schedule).
Git
We use GitHub classroom to provide you with the initial agent code. GitHub is a code hosting platform for version control and collaboration. You need to join the GitHub classroom and use it for developing and sharing your code, and for storing and updating all the deliverables in this project. In order to understand how to do that, we introduce you to some basic readings and a tutorial to gain knowledge of how to use git.
Git Commands
You can either do just the basics reading or do the interactive tutorial, or both. There is also a more in-depth explanation of each command in the third page.
The absolute basics (reading): https://www.simplilearn.com/tutorials/git-tutorial/git-commands.
The basics (an interactive tutorial!) - https://learngitbranching.js.org/.
If you want to know more (not required): Everything on Git.
Git Merging and Conflicts
https://www.simplilearn.com/tutorials/git-tutorial/merge-conflicts-in-git
Git Best Practices
https://www.geeksforgeeks.org/best-git-practices-to-follow-in-teams/
Dialogflow
We use Google’s Dialogflow for transcribing spoken user utterances into text by means of Automatic Speech Recognition (ASR), and for classifying these texts by means of intent recognition (NLU). One of your main tasks will be designing an intent scheme and adding entities for making sense of what a user says. You will need to specify these in your Dialogflow agent, which you need to create at the start of the project (only one per team).
Dialogflow is a powerful and user-friendly tool to support building a conversational agent but needs some investment on your end to get acquainted. Git is a common tool used by many coding teams worldwide to develop code in tandem and facilitate its alignment. Getting to know git as part of this course will surely be of benefit to you in the long term. The resources we refer to below should provide you with adequate support to use them in the remainder of the project. To make sure that you have the right level of understanding after going through the material, there are two quizzes in CANVAS that test your knowledge of the subjects. We have defined what areas will be tested on but feel free to read beyond those sections or other resources.
An Interactive Tutorial (Optional)
https://botflo.com/dialogflow-es-beginner-tutorial/
Best Practices
(until and not including ‘Protection of Consumer Practices’ section)
(In ‘Designing for Voice’ it mentions SSML, which will not be emphasized in this course)
https://cloud.google.com/dialogflow/es/docs/agents-design
What’s an Agent?
https://cloud.google.com/dialogflow/es/docs/agents-overview
Intents
(all sections until and not including ‘Rich response message’ section)
https://cloud.google.com/dialogflow/es/docs/intents-overview
Entities
(until and not including ‘Session entities’ section)
https://cloud.google.com/dialogflow/es/docs/entities-overview
HTML Bootstrap Library
Bootstrap is a powerful, open-source front-end framework for web development. Key features include:
Responsive Design: Bootstrap's grid system and pre-designed components enable easy creation of responsive websites.
HTML, CSS, and JS Components: Offers a wide range of reusable components like buttons, forms, and navigation bars.
Customization: Allows extensive customization with Sass variables.
Cross-Browser Compatibility: Ensures consistency across different browsers and devices.
JavaScript Plugins: Includes various plugins for enhanced functionality.
Community and Documentation: Backed by a strong community and comprehensive documentation.
Mobile-First Approach: Prioritizes mobile devices in design strategies.
This framework simplifies web development, making it accessible for beginners while still powerful for experienced developers. Here is a link to the Documentation for more information: https://getbootstrap.com/docs/5.3/getting-started/introduction/ .
Also read through our Visual Support: A Guide.
Prolog
You will develop your recipe recommendation agent using MARBEL and SWI Prolog. The MARBEL agent implements a dialog management engine that you will use. You do not need to change this agent. You are, however, allowed to modify it if you like. The focus will be mostly on using Prolog to provide the agent with the knowledge it needs and to make it smarter by providing it with some logic related to its recipe recommendation task.
Prolog is a rule-based programming language based on symbolic logic. It is commonly used in Artificial Intelligence and Computational Linguistics. To understand Prolog, you should have familiarized yourself with its key concepts and structures using the book https://www.let.rug.nl/bos/lpn//lpnpage.php?pageid=online. This book covers fundamental topics like facts, rules, queries, unification, proof search, recursion, lists, arithmetic, definite clause grammars, and more. It also delves into more advanced topics such as cuts and negation. We briefly summarize here some of the core concepts for your convenience.
Logic-Based Programming: Prolog is fundamentally different from procedural languages like C or Python. It is based on formal logic, making it well-suited for tasks that involve rules and constraints, such as solving puzzles or processing natural language.
Facts, Rules, and Recursion: The core of Prolog programming involves defining facts and rules. Facts are basic statements about objects and/or their relationships. Rules define relationships between facts using basic logical relations such as conjunction, disjunction, and negation. The fact that rules can be recursive is what gives Prolog its power as a programming language. Recursion can be used, for example, for iterating over frequently used data structures in Prolog such as lists.
Lists and Arithmetic: Lists are fundamental data structures in Prolog. Prolog offers a range of built-in predicates for list manipulation. It also provides built-in support for arithmetic operations. Because Prolog’s basic form of computation is based on term matching, which does not support efficiently doing math, care must be taken to use the right operators when handling numbers in Prolog.
Pattern Matching and Unification: Prolog core form of computation consists of pattern matching with the aim of unifying Prolog terms. Unification of two terms is a fundamental operation in Prolog, which, if it succeeds, returns substitutions for Prolog variables. When these substitutions are applied to the terms (and the variables instantiated), the result would be two identical terms.
Backtracking: Prolog uses backtracking to evaluate the rules in a program to find solutions to problems. If one trace (part of a search tree) fails, Prolog automatically backtracks to find and try alternative options that have not yet been explored to continue searching for a solution.
Advanced Features: Prolog provides advanced features like the cut operator. This operator can be used for controlling the backtracking process, mainly to increase efficiency of Prolog programs.
Definite Clause Grammars (DCGs): These are used in Prolog for parsing and generating natural language constructs, making it a powerful tool for language-related applications.
Applications: Prolog is widely used in AI for tasks such as expert systems, natural language processing, and theorem proving, owing to its ability to handle complex symbolic information and logical constructs efficiently.