By Ford James
Published September 23, 2026
Main Facts
Embark Studios is once again pushing the boundaries of procedural animation and artificial intelligence in multiplayer shooters. With the upcoming release of Arc Raiders’ largest content drop to date—the "Frozen Trail" update, scheduled to launch on October 8, 2026—players will face a terrifying new mechanical threat known simply as "The Bully."
Following in the footsteps of the notorious Leaper, the Bully is the latest ground-based adversary in Arc Raiders to be engineered using advanced machine-learning (ML) techniques. Unlike traditional scripted enemies whose movement paths and reactions are hardcoded by developers, ML-driven enemies in Arc Raiders learn their behaviors through simulated rewards and recognition systems. This unique approach allows them to adapt dynamically to the game’s complex physics engine, terrain obstacles, and player interactions.
The Frozen Trail update will roll out as a free expansion across all major platforms, including PlayStation 5, Windows PC, and Xbox Series X, bringing a wave of new tactical challenges, mechanics, and unpredictable combat encounters to the topside world.
Chronology of Technological Evolution: From Leaper to Bully
To understand the significance of the Bully, one must look back at how Embark Studios pioneered machine learning for its mechanical roster.
Earlier this year at the Game Developers Conference (GDC), Martin Singh-Blom, the machine learning research lead at Embark Studios, lifted the curtain on how the studio crafts its most menacing foes. He detailed how the Leaper—a towering, multi-legged hazard known for terrorizing players topside—uses reinforcement learning. Instead of being programmed to step in a specific sequence, the Leaper’s virtual brain is rewarded for successful locomotion and goal pursuit. This training allows the enemy to act with organic fluidity and, crucially, to overcome unexpected catastrophic failures, such as losing a limb mid-combat.
While the Leaper established the viability of machine-learning locomotion in a live-service shooter environment, Embark Studios is taking the concept further. During a virtual press pre-briefing hosted ahead of the Frozen Trail reveal, media outlets and creators were given their first live look at the Bully in action.
While smaller in stature than the towering Leaper, the Bully makes up for its lack of height with sheer bulk, relentless aggression, and an unyielding desire to close the distance between itself and the player. Scheduled to arrive alongside the rest of the Frozen Trail update on October 8, the Bully represents the next generation of Embark’s adaptive adversary pipeline.
Supporting Data and Technical Architecture
The technical underpinnings of Arc Raiders’ machine-learning enemies represent a paradigm shift in how artificial intelligence handles physical space in video games.
During the pre-briefing Q&A session, Arc Raiders Executive Producer Aleksander Grøndal elaborated on the mechanics behind these physics-driven foes. According to Grøndal, machine learning is uniquely suited for entities equipped with legs.
"Machine-learning enemies are best suited to when they have legs, when they can learn to walk," Grøndal explained. "We have a couple of different platforms in which we train, and the best results we’ve had so far are the ones that have legs we can manipulate as players, and see how they adapt to any situation; losing a leg or getting stuck, falling over or tumbling, or things like that which create those fun and dynamic moments."
The Bully, specifically, has been designed to exploit verticality and uneven terrain. Because it is heavily grounded and stocky, its neural network training focuses intensely on terrain traversal. Whether navigating rocky ruins, steep inclines, or narrow choke points, the Bully calculates its movement in real-time, ensuring that players cannot easily exploit pathfinding bugs or static geometry to escape.
Furthermore, the introduction of the Bully coincides with a brand-new tether system debuting in the Frozen Trail update. This system fundamentally alters how players interact with enemy physics, allowing combatants to manipulate, pull, and disrupt these machine-learning behemoths in ways previously impossible in the genre.
Official Responses and Developer Insights
Embark Studios has been remarkably transparent about the experimental nature of integrating machine learning into a fast-paced shooter. Speaking candidly about the development hurdles, Executive Producer Aleksander Grøndal acknowledged that training artificial intelligence is far from an exact science.
When asked about the studio’s long-term roadmap for machine learning and whether fans can expect to see it applied to an even broader array of enemies, Grøndal offered a measured perspective:
"We see machine learning as an emerging technology, which is still in its infancy to some degree. It’s still a bit of an advanced research task on our end. The interesting thing about it is that you can’t control it super well. We try to teach it how to behave, and sometimes that doesn’t make sense at all. Sometimes we need to update the model to fix particular issues with it."
Despite these unpredictable hurdles, Embark remains committed to utilizing the technology as a core pillar of enemy design philosophy. Grøndal emphasized that these entities are carefully curated to fill specific tactical slots within the game’s ecosystem:
"Enemies that use machine learning in Arc Raiders are supposed to fill archetype roles in the roster. As the technology becomes better, and we learn more about it, we’ll utilize it in the best possible way to create unique experiences."
This iterative loop—where developers train models, observe erratic or brilliant emergent behaviors, and refine the parameters—allows Embark to sidestep the predictable patterns that often plague traditional AI opponents in modern video games.
Implications for the Future of Arc Raiders and the Industry
The introduction of the Bully and the refinement of Embark’s machine-learning pipeline carry significant implications for both Arc Raiders and the broader gaming industry.
1. Emergent Gameplay and Replayability
For Arc Raiders, the primary goal of machine learning is the generation of unscripted, highly cinematic combat moments. Traditional game AI relies on finite state machines and predefined animation trees, which players often learn to exploit over hundreds of hours of gameplay. In contrast, an ML-driven enemy like the Bully or the Leaper reacts organically to physics disruptions. If a player shoots the Bully’s leg or causes it to stumble over debris, the resulting fall is not a canned animation; it is a real-time calculation based on the neural network’s trained understanding of balance. This ensures that no two firefights play out identically.
2. A Shift in Industry Standards
While Embark Studios is quick to point out that these systems are still in an advanced research phase, the success of machine-learning locomotion in Arc Raiders could serve as a watershed moment for the industry. For years, game developers have wrestled with the uncanny valley of procedural animation. By utilizing reinforcement learning to teach digital characters how to walk, stumble, and recover, studios can reduce the massive overhead required for hand-animated motion capture while simultaneously delivering superior environmental reactivity.
3. Heightened Psychological Pressure on Players
The thematic branding of the Bully is entirely accurate to its mechanical purpose. By combining relentless pursuit routines with adaptive terrain traversal, the Bully is engineered to deny players safety and comfort. In a survival-extraction shooter where resource management and positioning are paramount, facing an enemy that refuses to give up chase—and actively learns how to navigate around defensive bottlenecks—raises the stakes considerably.
Conclusion
As the countdown to October 8 ticks away, anticipation for the Frozen Trail update is reaching a fever pitch. With its free release on PlayStation 5, Windows PC, and Xbox Series X, players will soon discover whether their tactical strategies can withstand the relentless, machine-learned assault of the Bully.
Embark Studios continues to prove that it is willing to take calculated risks on cutting-edge technologies. If the Leaper was an impressive proof of concept, the Bully stands to be the definitive test of whether machine learning can permanently redefine how we fight our digital adversaries.
