Halo 2 Game Reboot

Introduction

This report examines the Enemy AI feature in Halo 2. It begins with an overview of the game, followed by an analysis of the feature, examples of its evolution in recent games, a review of relevant literature, and a proposal for its implementation in future releases.

Halo 2 developed by Bungie and published by Microsoft Game Studios for the Xbox was released on November 9th, 2004. Within the first-person shooter (FPS) genre, Halo 2 quickly became an iconic game praised for its innovative multiplayer, compelling narrative, and technical advancements.

Using an improved version of the Halo engine (The Blam Engine) the game provided enhanced graphics, immersive sound design and real time cutscenes. Players play as two characters throughout the game, Master Chief a Spartan Super soldier, and the Arbiter, a disgraced alien commander. This allowed for a dual perspective storyline that deepens the lore of the series. Encounters with multiple enemy types, and large-scale battles enhance the gameplay experience.

One of the notable achievements of Halo 2 was the implementation of Xbox Live. This allowed for seamless online multiplayer matches, using a combination of advanced AI (Artificial Intelligence) for the enemy behaviour and the online features provided by Xbox Live. This set Halo 2 apart from its competition and secured its place in gaming history.

Specific Feature: Enemy AI in Halo 2

The specific feature chosen for analysis is Halo 2s Enemy AI, a defining element in its success. Bungie used behaviour trees to create unpredictable and dynamic combat situations. Utilising AI systems allowed for enemies to make realistic decisions, such as, taking cover from open fire, coordinating attacks with allies, and flanking behind players. An example of this is ‘elite enemies’, who use a range of tactical behaviours allowing them to adapt their strategy in response to players actions. Advanced AI engagements allow for the games encounters to feel more realistic, improving player experience.

The complexity of the AI was created by using a hierarchy of finite state machines allowing behaviours to adapt and stack. Grunts which are lower tier enemies can run away when their elite commander is killed. These interactions contribute to the combat intelligence, reactive components, and enhance gameplay.

Additionally, Halo 2's AI transformed combat encounters into more than standard firefights. With the introduction of dynamic, ever-evolving challenges, each battle feels unique, requiring players to quickly adapt their tactics to be successful.

Enhancing Gameplay Through AI

The use of AI behaviours such as retreating and flanking, added a new layer of realism most other games at the time. Elites typically coordinate attacks with additional nearby units, creating situations that force players to carefully consider their next move. These AI decisions encourage players to experiment with the game’s assets, taking into account each weapons strengths and weaknesses in all scenarios.

Furthermore, AI structure design allows for clear distinctions between the behaviour and roles of enemy factions. For example, Jackals use energy shields to defend against snipers, whereas Brutes rely on their strength and aggression to overwhelm the player. This design fortifies the narrative element of the Covenant as a coalition of diverse species which each contribute unique strengths.

There are however some AI weaknesses, such as pathfinding errors and occasional predictable behaviour, although this contributes to the games charm. This is because the enemies feel relatable and grounded, mirroring the imperfect decision-making of real-life combatants. AI is a storytelling device that adds depth and personality to the alien forces that the player must face.

Examples in More Recent Games

The influence of Halo 2’s AI behaviour can be found in many modern titles, for example, in The Last of Us Part 2. Developers, Naughty Dog use AI features capable of complex behaviour such as communicating with teammates, flanking, and the ability for the AI to react emotionally to events like death or injury.

Another example of Halo 2s enemy Ai in recent games is Doom Eternal, released in 2020 by Id Software. Doom Eternal uses AI that prioritises adaptability and aggression whilst creating a symbiotic relationship between the players movement and the enemy’s strategy. This creates a relentless combat experience that mirrors the intensity of Halo 2s gameplay, forcing players to constantly react and adapt.

Similarly, Far Cry 5 produced by Ubisoft in 2018 utilises AI features that dynamically interact with the games open world environment. Enemies coordinate ambushes, use vehicles, and strategy to exploit cover, showcasing a level of tactical sophistication similar to Halo 2’s design.

Titanfall 2 by Respawn Entertainment released in 2016 features highly adaptive AI, with enemies employing tactical manoeuvres to challenge players. Its fast-paced action of pilot gameplay and mech combat displays the evolution of Halo 2s combat principles.

The Shadow of Mordor released in 2014, and the Shadow of War released in 2017 by Monolith Productions utilised Halo 2’s influence with the Nemesis system. This AI feature allows enemies to remember and react to the players previous actions, creating a personalised and unique gameplay. The Nemesis system shows an evolution of the engaging encounters that were central to Halo 2.

Assassin’s Creed Odyssey released in 2018 brings an AI bounty hunter feature that pursues the player across the games open world. The hunters adapt to the player's tactics and playstyle, echoing Halo 2’s approach to designing AI that responds dynamically to player behaviour.

Finally, Halo Infinite released in 2021 was a direct successor to Halo 2, building on advancements in enemy AI since 2004. The enemies in Halo Infinite demonstrate dynamic behaviour with unique dialogue that is responsive to the players actions. The game’s open-world design amplifies these interactions, creating varied and engaging encounters.

Collectively, these modern game titles highlight the reach of influence Halo 2s AI design, laying the foundation for more immersive gaming experiences. Adaptive enemy behaviour and emergent gameplay in Halo 2 has shaped the development of modern AI systems which creates greater complexity and engagement for players. Overall, this reflects the importance of Halo 2 as a pivotal moment the evolution of game design.

Insights from Game Studies Literature

Multiple academic sources on AI in video games highlight the importance of behaviour trees and adaptive systems offering valuable insights. The first source, “Implementation of Behaviour Tree in Halo 2” offers a detailed analysis of the hierarchical and modular system within the game. The authors explore how behaviour trees allow for adaptive decision making, enhancing the unpredictability of enemy encounters. It is stated that:

"By implementing a behavior tree, it is also possible to create a personalized behavior for each type of enemy. The parent node can act as a generalized behavior and the children nodes can act as a specialized behavior for each type."

As a result, adaptability played a vital role in immersing players, whilst keeping a good level of technical efficiency with the limitations of the Xbox console hardware. In addition, the use of nodes creates a unique and compelling gameplay experience that was not nearly as extensive for its time period. (Smith, 2020)

Furthermore, I found another source from an industry perspective, “Handling Complexity in Halo 2 AI” written by Damian Isla. Damian Isla presented at the GDC 2005 Proceedings, where they offered an in depth look at the challenges faced by the development team. The article shows the importance of balancing complex AI routines with the limitations and constraints of the hardware during the time period. Damian Isla stated:

"It is not enough that the AI be able to do it a lot of things, it is equally important that they do all those things right, at the right times, and in a way that does not break the illusion of life, or threaten the player's understanding of the AI's intentions or motivations."

This highlights the importance of developing AI that can not only possess a wide range of behaviours but also executes them at the appropriate time to keep the player immersed. (Isla, 2023)

Expanding my research into Halos AI I found an article written by Pérez et al called “A Survey of Behaviour Trees and Their Applications for Game AI”. This paper explores how the scalability and modularity of behaviour trees are a preferred choice for developers that are looking for adaptive AI systems. Pérez et al. states:

"Behaviour Trees first made a splash as the ‘next big thing’ at the 2005 Game Developers Conference (Kirby, 2011). They had already been used in Halo 2 (2004), made another appearance in in Spore (2008), and began to gain ground towards acceptance as a mainstream approach for non-player character (NPC) AI."

The research and work done in this article underscores the ongoing impact Halo 2 has had as a model for integrating behaviour trees in commercial games. (McQuillan, 2017)

Finally, an analysis by HowStuffWorks ranking the Halo Games with artificial intelligence as a key factor, recognises Halo 2 as a pivotal entry due to its groundbreaking enemy AI.

The article commends the game for its strong balance of challenge and replay ability. The enemy AI within Halo 2 displayed an unparallelled level of challenge which then set a benchmark for the series. The expectations from players and developers alike were reshaped as a result. This recognition further solidifies the games legacy as a pioneer in AI innovation. (Steinberg, 2017)

Furthermore, a review for the game was left shortly after released in November 2004 by Muck0_Man stating that:

"Halo 2 has an average length and when you get to the end you'll be yearning for Halo 3. The game takes an average player about 12 hours, but it's so good you'll want to play it over and over again."

This emphasises the success of Halo 2 with its use of engaging gameplay providing replay value, which ultimately contributed to the game’s popularity. (_Man, 2004)

Collectively, these sources provide a strong understanding of Halo 2’s Enemy AI, highlighting its narrative, technical, and gameplay contributions. As a result of integrating modular and scalable AI systems, Halo 2 pushed the boundaries of what was considered feasible at the time, influencing the design principles of subsequent games. These advancements create a strong foundation for reimaging Halo 2 in a contemporary reboot whilst ensuring that its legacy continues to inspire game design.

Proposed AI Enhancements for a Halo 2 Reboot

In a contemporary reboot of Halo 2, the enemy AI could use machine learning to further improve adaptability. Machine Learning, a branch of AI mimics human thinking whereas AI mimics human interactions and experiences. Machine learning enables change and growth when exposed to new data without it being explicitly programmed for. This adaptive technology allows for a much more personalised experience.

Utilising machine learning systems could allow for enemies to analyse player behaviour patterns in real time and adjust their tactics dynamically. For example, enemies could behave more aggressive or defensive dependant on the player’s performance which as a result creates a more challenging and personalised experience.

In addition, integrating neural networks could allow for AI characters to learn and evolve over time. In relation to the series, Elite enemies could develop new strategies after multiple battles and encounters with the player, resulting in fresh and unpredictable combat. As a result, this would replicate the unpredictability of real-world combat situations and offer the player consistent challenges.

Another potential improvement for a Halo 2 reboot could be utilising procedural AI generation. By using this approach, enemy strategies and behaviours could be targeted to individual player styles to ensure that each playthrough feels unique. A system like this could also support dynamic difficulty adjustments to allow the game to remain accessible whilst still offering a rewarding challenge for advanced and veteran players.

To improve the reboot further, the implementation of squad-based AI dynamics could drastically elevate the games level of immersion. Allowing enemy units to collaborate and communicate strategically, individual AI programmed enemies could act as part of a team. For example, Grunts could offer suppressive fire whilst Elites flank the player. Another example is that Jackals could coordinate to create shield walls in a response to player aggression. A level of teamwork like this would increase the complexity of combat and reward players who use tactical strategies to counter enemy attacks.

A reboot of Halo 2 could be enhanced using environmental awareness for AI. Using advanced pathfinding algorithms enemies could interact intelligently with the environment around them. For example, using cover effectively, gaining high ground, or retreating to regroup when overpowered. This would make the encounters feel realistic and engaging as the player would need to adapt to the battlefield to succeed.

Lastly, advancements in natural language processing could result in more immersive interactions with AI characters. Enemies could deliver taunts and respond to players actions with unique dialogue, further blurring the line between human and AI like behaviour. In addition, enemies could react vocally by expressing fear or overconfidence, depending on the situation. This adds personality to the enemies making them feel less like lifeless entities. Interactions like this could deepen the emotional investment in fights reinforcing the iconic nature of Halo 2’s encounters.

Conclusion

Halo 2’s AI behaviour remains a landmark achievement in game design, demonstrating the potential of behaviour trees and adaptive systems. Through examination of the implementation and influence on modern game titles, it is clear that Halo 2 set a new standard in the gaming world. Halo 2’s innovative use of behaviour trees and hierarchical finite state machines created a new standard for producing realistic and engaging enemy encounters.

A reboot using machine learning would not only uphold the games legacy but push the boundaries of player immersion further. Ultimately, using modern AI techniques such as machine learning, procedural generation, neural networks, and natural language processing would redefine the possibilities of enemy design, resulting in a whole new outlook on gaming for the new generation of players.

The legacy of Halo 2’s AI represents how a well-designed system can change the expectations for interactive gameplay across the industry. Behaviour trees and hierarchical finite state machines not only elevated player experience but also set a benchmark for intelligent and adaptive enemy behaviour. The addition of AI capable of responding to player actions made combat encounters feel unique and authentic, delivering an outstanding a level of immersion for its time.

This innovation was not only technical but also thematic, the AI’s ability to tell the difference between the behaviours of different enemy factions enhanced the narrative of the Covenant. The interplay between storytelling and gameplay was heightened with the enemy AI working as both a narrative device and a gameplay mechanic, reinforcing the stakes and tension inside the Halo universe.

Halo 2’s AI has had an influence that can still be found in modern games that have adopted a similar system to produce immersive and evolving encounters. Through dynamic pathfinding, procedurally generated, or squad-based tactics; developers continue to build on the foundations created by Halo 2. The games legacy shows the importance of artificial intelligence innovation to improve not only the gameplay mechanics but also the storytelling potential in video games.

References

Isla, D. (2023) GDC 2005 proceeding: Handling complexity in the halo 2 AI, GDC 2005 Proceeding: Handling Complexity in the Halo 2 AI. Available at: https://www.gamedeveloper.com/programming/gdc-2005-proceeding-handling-complexity-in-the-i-halo-2-i-ai (Accessed: 03 January 2025).

McQuillan, K. (2017) A survey of behaviour trees and their applications for Game Ai a survey of behaviour trees and their applications for Game Ai, A Survey of Behaviour Trees and their Applications for Game AI A Survey of Behaviour Trees and their Applications for Game AI. Available at: https://www.academia.edu/33601149/A_Survey_of_Behaviour_Trees_and_their_Applications_for_Game_AI_A_Survey_of_Behaviour_Trees_and_their_Applications_for_Game_AI (Accessed: 03 January 2025).

Smith, D. (2020) Implementation of behavior tree in Halo 2 - ITB, Implementation of Behavior Tree in Halo 2 - ITB. Available at: https://www.readkong.com/page/implementation-of-behavior-tree-in-halo-2-itb-9414506 (Accessed: 03 January 2025).

Steinberg, N. (2017) Ranking 9 ‘Halo’ games from worst to best, HowStuffWorks. Available at: https://electronics.howstuffworks.com/ranking-the-halo-games-from-worst-to-best.htm (Accessed: 03 January 2025).

_Man, M. (2004) Halo 2 – Review, A console FPS worthy of this long review. Available at: https://gamefaqs.gamespot.com/xbox/562116-halo-2/reviews/81512 (Accessed: 03 January 2025).