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This course features Coursera Coach!

A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course.

In this advanced-level course, you will explore sophisticated AI techniques for creating realistic, dynamic, and intelligent behaviors in Unity. Starting with crowd simulation, you will learn how to simulate large groups of agents moving as one, as well as how to implement flocking behavior for AI groups. The course takes you through the process of creating goal-driven AI using Goal-Oriented Action Planning (GOAP), and introduces behavior trees to structure complex decision-making systems.

The course begins with a focus on crowd simulation, where you will learn how to simulate both fleeing and flocking behaviors in groups of agents. Then, you will dive into Goal-Oriented Action Planning (GOAP), creating intelligent agents that plan their actions dynamically based on environmental conditions. Additionally, you’ll explore behavior trees, a powerful tool for organizing AI actions and decision-making, allowing your agents to execute tasks like navigation, combat, and interaction with the game world.

Designed for developers looking to level up their AI development skills, this course requires prior experience with Unity and basic AI concepts. Whether you're developing strategy games, simulation games, or action games, the techniques learned in this course will help you build more complex and engaging AI systems for your games. By the end of the course, you will be equipped to implement highly adaptive AI for a variety of game environments.

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Syllabus

Crowd Simulation
In this module, we will cover advanced crowd simulation techniques, from basic flocking algorithms to complex behaviors like fleeing and goal-oriented movement. You’ll create dynamic, realistic crowds and learn to control their movements within game environments.
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Career center

Learners who complete Advanced AI Techniques and Behavior in Unity will develop knowledge and skills that may be useful to these careers:
Artificial Intelligence Programmer
An Artificial Intelligence Programmer is a specialist responsible for designing, implementing, and optimizing AI systems within software applications and games. This role involves crafting the intelligence that drives non-player characters, enemy behaviors, and dynamic world interactions. For an aspiring Artificial Intelligence Programmer, this course offers in-depth exploration of sophisticated AI techniques crucial for success. Learners will delve into Unity, a prevalent engine for creating interactive experiences, mastering advanced crowd simulation, Goal-Oriented Action Planning (GOAP), and behavior trees. These specific modules enable the creation of highly adaptive and engaging agent behaviors, directly transferable to developing complex AI for various game genres or simulations. The insights gained from structuring complex decision-making systems and implementing goal-driven agents are directly applicable to the daily tasks of this profession.
Gameplay Programmer
A Gameplay Programmer implements the core logic and interactive features of a game, including player controls, game mechanics, and the behavior of game entities. This often involves working closely with AI systems to bring the game world to life. For an aspiring Gameplay Programmer, this course is highly relevant, focusing on advanced AI techniques specifically within the Unity engine. The curriculum provides practical experience with crowd simulation, Goal-Oriented Action Planning (GOAP), and behavior trees, directly applicable to creating dynamic and responsive in-game characters. Mastering these systems helps in developing intelligent enemy AI, friendly non-player characters, or environmental agents that contribute to engaging gameplay. The ability to structure complex decision-making and implement goal-driven actions efficiently is a core asset for any professional in this role.
Serious Games Developer
A Serious Games Developer creates interactive digital experiences for purposes beyond pure entertainment, such as education, training, healthcare, or military simulation. These applications often require highly realistic and intelligent agent behaviors. For a Serious Games Developer, this course is invaluable due to its focus on sophisticated AI techniques for creating dynamic and intelligent behaviors in Unity. The principles of crowd simulation, Goal-Oriented Action Planning (GOAP), and behavior trees are directly applicable to building immersive and adaptive training scenarios. Whether simulating emergency responses, strategic decision-making, or complex social interactions, the ability to create agents that plan and execute actions based on changing goals and environmental conditions is crucial for developing effective serious games that provide realistic and engaging learning or training outcomes.
Educator Game Development
An Educator Game Development teaches students the principles, tools, and practices required to create video games, often specializing in areas like programming, design, or art. For an Educator Game Development, this course is highly relevant for enhancing their curriculum and pedagogical approach to artificial intelligence in games. The advanced AI techniques covered, such as crowd simulation, Goal-Oriented Action Planning (GOAP), and behavior trees in Unity, are fundamental topics in modern game AI. Mastering these concepts allows an educator to provide up-to-date, practical instruction, equipping their students with essential skills for developing complex and engaging AI systems. This particular course's focus on practical implementation within Unity makes it an excellent resource for structuring hands-on learning experiences and demonstrating intricate AI behaviors.
Game Designer
A Game Designer conceptualizes and develops the core mechanics, rules, and overall player experience of video games. While often not directly coding, an understanding of technical constraints and possibilities, especially concerning artificial intelligence, is invaluable. For a Game Designer, this course offers a unique perspective on what is achievable with in-game intelligence, helping them design more sophisticated and engaging challenges for players. The modules on crowd simulation, Goal-Oriented Action Planning (GOAP), and behavior trees provide insight into how dynamic and intelligent character behaviors can be crafted, enabling designers to envision and specify complex AI interactions. Understanding these advanced techniques empowers a designer to articulate their vision more effectively to programmers and to push the boundaries of interactive character design, leading to richer game worlds and experiences.
Simulation Engineer
A Simulation Engineer designs, develops, and deploys computational models and software to simulate real-world systems or processes across various industries such as defense, manufacturing, or logistics. These simulations often require intelligent agents and dynamic behaviors. For a Simulation Engineer, this course may be useful as it delves into advanced AI techniques highly relevant to creating realistic and adaptive simulated entities. The focus on Unity, a versatile platform, combined with concepts like crowd simulation, Goal-Oriented Action Planning (GOAP), and behavior trees, provides a strong foundation for modeling complex system interactions. Understanding how to create agents that plan actions dynamically based on environmental conditions and execute tasks like navigation can be directly translated to developing sophisticated simulation scenarios, enabling more accurate and insightful analyses of complex systems. An advanced degree is often typical for this role.
Character Technical Director
A Character Technical Director oversees the technical aspects of character production in animation, visual effects, and games, ensuring characters function correctly within the digital environment. This includes rigging, skinning, and sometimes aspects of character AI or crowd systems. For a Character Technical Director, this course may be helpful in developing a deeper understanding of how advanced AI techniques drive character behavior within Unity. Knowledge of crowd simulation, specifically flocking and fleeing behaviors, directly impacts how large groups of characters are handled. Furthermore, understanding behavior trees and Goal-Oriented Action Planning (GOAP) allows for better integration of character rigs and animations with the AI systems that dictate character actions and decision-making, ensuring believable and responsive performances in complex scenes.
Robotics Software Engineer
A Robotics Software Engineer develops the programming and algorithms that control autonomous robots, enabling them to perceive, decide, and act in the physical world. This role demands a deep understanding of intelligent decision-making and interaction. For a Robotics Software Engineer, this course may be helpful due to its focus on behavior trees and Goal-Oriented Action Planning (GOAP). These paradigms are fundamental to structuring complex robotic actions and decision-making processes, allowing robots to plan and execute tasks dynamically based on environmental conditions and changing goals. While the course uses Unity for game environments, the underlying principles of creating intelligent agents, managing complex behaviors, and executing tasks like navigation are directly transferable to programming real-world robotic systems. An advanced degree is often typical for this role.
Technical Director Research and Development
A Technical Director Research and Development explores new technologies and methodologies to push the boundaries of artistic and technical capabilities in areas like film, games, or visualization. This often involves prototyping advanced systems. For a Technical Director Research and Development, this course may be useful in exploring sophisticated AI techniques for creating dynamic and intelligent behaviors within Unity. The curriculum's focus on crowd simulation, Goal-Oriented Action Planning (GOAP), and behavior trees provides concrete methods for prototyping advanced agent systems. Understanding these techniques enables the exploration and integration of cutting-edge AI for various interactive applications, allowing them to assess and implement innovative solutions for complex decision-making and character interaction in future projects. An advanced degree is sometimes typical for this role.
Tools Programmer
A Tools Programmer develops software and utilities that enhance the productivity of other developers, artists, and designers within a game or software development studio. These tools often integrate with existing systems, including AI frameworks. For a Tools Programmer, this course may be helpful as it provides an advanced understanding of AI techniques within Unity. This knowledge is crucial for creating effective tools to visualize, edit, or debug AI behaviors such as crowd simulations, GOAP plans, or behavior tree structures. Understanding the inner workings of these systems allows for the development of intuitive and powerful tools that streamline the development process for AI programmers and designers, ensuring efficient creation and iteration of intelligent agent behaviors for game environments.
Software Engineer
A Software Engineer designs, develops, and maintains software applications across various platforms and industries. In roles that involve complex system behaviors or intelligent automation, a strong grasp of AI principles is increasingly sought after. For a Software Engineer interested in specializing in intelligent systems, this course may be helpful by providing a practical foundation in advanced AI techniques using Unity. While Unity is a game engine, the core concepts of crowd simulation, Goal-Oriented Action Planning (GOAP), and behavior trees are broadly applicable to modeling intelligent agents and decision-making in other software domains. The ability to structure complex actions and create dynamic, adaptive behaviors can be adapted for applications beyond entertainment, such as intelligent automation, data simulation, or intricate system control.
Level Designer
A Level Designer constructs the environments, challenges, and experiences players encounter within a game. This includes placing enemies, defining mission objectives, and orchestrating scenarios where AI characters must react intelligently. For a Level Designer, this course may be useful in deepening their understanding of how intelligent behaviors are implemented in Unity. Knowledge of crowd simulation, Goal-Oriented Action Planning (GOAP), and behavior trees allows a designer to create more dynamic and believable levels. They can better anticipate AI movements, design spaces that complement complex decision-making, and craft encounters that leverage the full capabilities of goal-driven and behavior-tree-controlled agents, leading to richer, more interactive gameplay experiences.
Technical Artist
A Technical Artist bridges the gap between art and programming, developing tools, pipelines, and technical solutions for game art production, often including asset setup for animation, physics, or AI. For a Technical Artist, this course may be useful by providing a deeper understanding of how AI systems function within Unity. While not directly creating the AI code, understanding the mechanics of crowd simulation, Goal-Oriented Action Planning (GOAP), and behavior trees allows a Technical Artist to better prepare assets, optimize scenes, and troubleshoot issues related to character animation and behavior. This knowledge helps in creating more efficient workflows and ensuring that artistic vision integrates seamlessly with the underlying AI architecture, contributing to more robust and believable in-game character performance and interaction.
Research Scientist, Artificial Intelligence
A Research Scientist Artificial Intelligence conducts theoretical and applied research to advance the state of the art in AI, developing new algorithms, models, and techniques. This role often involves exploring novel ways to create intelligent behaviors. For a Research Scientist Artificial Intelligence, this course may be useful by showcasing practical implementations of advanced AI techniques like Goal-Oriented Action Planning (GOAP) and behavior trees within a common development environment like Unity. While primarily focused on application, understanding robust, implemented systems can inform theoretical work and highlight areas for future research in areas such as multi-agent systems, dynamic planning, or behavioral modeling. The course provides insight into how complex decision-making is structured and executed in a dynamic environment. An advanced degree is typically required for this role.
Machine Learning Engineer
A Machine Learning Engineer designs, builds, and deploys machine learning models and systems that enable applications to learn from data and make predictions or decisions. While distinct from traditional AI rule-based systems, M.L. engineers often integrate with or develop intelligent agents. For a Machine Learning Engineer, this course may be useful by providing a conceptual framework for agent behavior and decision-making, using techniques like Goal-Oriented Action Planning (GOAP) and behavior trees. Understanding these structured approaches to AI can complement data-driven machine learning, especially in hybrid systems where symbolic AI guides overall behavior and M.L. handles specific tasks. The course helps in understanding how agents interact within an environment and how complex actions are orchestrated, which can inform the design of M.L.-driven agents. An advanced degree is frequently typical for this role.

Reading list

We haven't picked any books for this reading list yet.
A practical guide to natural language processing (NLP) using Python, covering topics such as text classification, sentiment analysis, and machine translation. Suitable for beginners with some programming experience.
Provides a comprehensive overview of Unity, covering everything from the basics to advanced concepts. It great resource for both beginners and experienced Unity users.
Covers best practices for using Unity in production. It great resource for experienced Unity users who want to learn how to create high-quality games.
Covers shaders and effects in Unity. It great resource for beginners who want to learn how to create custom shaders and effects.
A comprehensive textbook that provides a broad overview of the field, covering topics such as problem-solving, learning, machine learning, and natural language processing. Suitable for both beginners and advanced learners.
A highly cited and influential book that focuses on deep learning, a subfield of AI concerned with constructing models for complex data. Covers theoretical concepts, popular algorithms, and practical applications.
A textbook that presents AI from a computational perspective, covering topics such as agents, knowledge representation, reasoning, and planning. Suitable for readers with a background in computer science or mathematics.
Covers game design patterns in Unity. It great resource for beginners who want to learn how to create reusable and maintainable game code.
Focuses on augmented reality game development in Unity. It great resource for beginners who want to learn how to create AR games.
A comprehensive textbook that covers probabilistic graphical models (PGMs), a powerful tool for representing and reasoning about complex systems. Suitable for advanced learners with a background in probability and statistics.
A short but powerful book that explores the potential benefits and risks of AI, as well as the ethical dilemmas that need to be addressed as AI becomes more advanced.
A comprehensive German-language textbook that provides a broad overview of AI, covering topics such as search, knowledge representation, and machine learning. Suitable for both beginners and advanced learners.
A French-language textbook that focuses on machine learning, a subfield of AI. Covers topics such as supervised learning, unsupervised learning, and deep learning. Suitable for beginners with some programming experience.
A classic textbook on reinforcement learning, a subfield of AI concerned with learning from interaction with the environment. Covers both theoretical concepts and practical algorithms, with a focus on real-world applications.
Provides an accessible introduction to the fundamental principles of AI as applied to computer games. It explains how to create NPCs with increasing levels of sophistication, covering perception, memory, and decision-making. This good starting point for beginners and those new to the field, offering a clear and easy-to-read overview of core Game AI concepts.
The third edition of Millington's book continues to be a strong resource for game AI. It updates and expands upon the foundational concepts, incorporating newer techniques and perspectives. It serves as both a solid introduction and a valuable reference for those seeking to understand the core algorithms and practices in Game AI. This commonly used textbook in academic settings.

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