Welcome to this page with a basic overview of basic the required background information for this project. Some of this information you have most likely seen before , either in the MAS course or previous courses in other courses, but some of it is will also be new to you. We expect you to have a decent understanding of the material listed below, as it is necessary to conduct be able to complete this project adequatelysuccessfully. This The background knowledge has to do with the software/tools and the programming languages we use in this project.
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.
Git
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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).
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Git
We use GitHub classroom to provide you with the initial agent code. GitHub is acode 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
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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 Basicsabsolute basics (reading): https://www.simplilearn.com/tutorials/git-tutorial/git-commands.
Basics The basics (an interactive tutorial!) - https://learngitbranching.js.org/More in Depth (Extra*) - .
If you want to know more (not required): Everything on Git.
Git Merging and Conflicts
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https://www.geeksforgeeks.org/best-git-practices-to-follow-in-teams/
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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)
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Logic-Based Programming: Prolog is fundamentally different from procedural languages like C or Python. It's based on formal logic, making it well-suited for tasks that involve rules and constraints, such as solving puzzles or processing natural language.
Facts and Rules: The core of Prolog programming involves defining facts and rules. Facts state basic assertions about objects or their relationships, while rules define the logic and conditions under which certain statements are true.
Backtracking and Recursion: Prolog uses backtracking to find solutions to problems. If a potential solution fails at some step, Prolog automatically backtracks to try different options. Recursion is also a prevalent concept, used for iterating over data structures like lists.
Pattern Matching and Unification: Prolog excels at pattern matching, where data structures are matched against patterns to extract information or verify conditions. Unification is a fundamental process in Prolog, used to make different terms identical through appropriate substitutions.
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.
Lists and Arithmetic: Prolog treats lists as fundamental data structures, and offers a range of built-in predicates for list manipulation. It also supports arithmetic operations, but in a way that's distinct from traditional programming languages.
Advanced Features: Prolog provides advanced features like cuts (which control the backtracking process) and negation, along with capabilities for database manipulation and file handling, making it versatile for various complex 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.
MARBEL
The MARBEL programming language is designed for creating agents in multi-agent systems. These agents are cognitive, deriving their actions from beliefs and MARBELs. Key features include:
Rule-Based System: MARBEL uses condition-action rules for decision-making.
Multi-Agent Systems: Requires a multi-agent system (MAS) file to launch and run an agent system.
Components: Includes knowledge representation files (Prolog .pl files), action specification files (.act2g), and module files (.mod2g) for event processing and decision-making.
Belief and MARBEL Bases: Agents have a belief base and a MARBEL base for maintaining their knowledge and objectives.
Event and Action Processing: MARBEL supports event modules to respond to events like percepts and messages, and action specification files inform agents about available actions.
Cognitive State Management: Cognitive state includes beliefs, MARBELs, percepts, and messages, which the agent uses to make decisions and interact with its environment.
Negation and Queries: Supports basic queries and their negation, allowing agents to reason about their environment and MARBELs effectively.
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HTML Bootstrap Library
Bootstrap is a powerful, open-source front-end framework for web development. Key features include:
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