SPIKE: An Adaptive Dual Controller Framework for Cost-Efficient Long-Horizon Game Agents

2026-05-18 · Source: Takara TLDR - Daily AI Papers · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Robotics & Autonomous Systems, Gaming & Interactive Media · Depth: Expert, quick

Summary

SPIKE is an adaptive dual controller framework designed for cost-efficient, long-horizon game agents operating in open-world, multimodal environments. It addresses the challenge of maintaining goal-directed behavior under tight token and latency budgets by strategically reusing reasoning. The framework features a low-frequency Strategic Controller for global planning, failure analysis, and recovery, complemented by a fast Reactive Controller for local execution within a strict token budget. An Event Trigger dynamically decides when to switch between reactive and strategic control based on visual changes, task progress, repeated actions, and failure signals. SPIKE also incorporates Hierarchical Memory, separating short-term experience in a State-Action Memory Bank (SA-MB) from structured evidence in a State Action Knowledge Graph (SA-KG). This design achieved a 5.0 percentage point (38.5% relative) improvement in Lite-100 success rate and a 9.3 point (75.6% relative) increase in Budgeted SR on the StarDojo Lite-100 split, while reducing token consumption by 54.9% and latency by 40.8%.

Key takeaway

For AI scientists developing long-horizon agents in resource-constrained environments, SPIKE's dual-controller and event-triggered architecture offers a robust blueprint. You should consider implementing separate strategic and reactive controllers, dynamically switching between them based on task-relevant events to optimize token usage and latency. This approach can significantly improve success rates and resource efficiency in complex, open-world simulations.

Key insights

SPIKE uses a dual-controller, event-triggered architecture with hierarchical memory for efficient long-horizon game agents.

Principles

• Reuse strategic reasoning across stable segments.
• Reinvoke strategic reasoning at event boundaries.
• Separate short-term experience from structured knowledge.

Method

SPIKE employs a Strategic Controller for global planning and a Reactive Controller for local execution, with an Event Trigger mediating control shifts. Hierarchical Memory (SA-MB, SA-KG) supports context retrieval for both controllers.

In practice

• Implement dual-controller architectures for complex tasks.
• Use event-based triggers to optimize resource use.
• Design hierarchical memory for varied context needs.

Topics

• SPIKE Framework
• Dual Controller Architecture
• Long-Horizon Game Agents
• Hierarchical Memory
• Event-Driven Reasoning

Best for: AI Scientist, Research Scientist, Robotics Engineer

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Editorial summary, takeaway, and curation by AIssential. Original article published by Takara TLDR - Daily AI Papers.