TABLE OF CONTENTS [TAP TO EXPAND]
- 01 Long-Horizon Multi-Step Agent Workflows
- 02 Static Token Budget Inefficiencies
- 03 Linear Budgeting Algorithms
- 04 Dynamic Entropy-Weighted Dispatcher
- 05 Scheduler Architecture
- 06 Adaptive Compute Allocation
- 07 Benchmark Results
- 08 Demonstrated Results
- 09 Entropy Overhead
- 10 Speculative Multi-Branch Scheduling
Long-Horizon Multi-Step Agent Workflows
Autonomous agent systems tackling deep code refactoring, complex mathematical proofs, or multi-day investigation tasks execute dozens of sequential reasoning branches with intermediate tool feedback.
Static Token Budget Inefficiencies
Fixed token quotas allocate identical reasoning compute to straightforward deterministic tasks as to high-entropy architectural forks. Critical reasoning branches truncate prematurely due to context exhaustion.
Linear Budgeting Algorithms
Evenly dividing token limits across workflow steps fails to anticipate decision forks where recursive tree search is genuinely required.
Dynamic Entropy-Weighted Dispatcher
HIRAX investigated an adaptive scheduler inside AURA Core that estimates the information entropy and branch uncertainty of each task node, dynamically routing compute quotas accordingly.
Scheduler Architecture
A branch entropy estimator calculates uncertainty metrics, while a dynamic compute router switches between lightweight models for deterministic tasks and deep reasoning models for high-uncertainty forks.
Adaptive Compute Allocation
When an agent enters a high-uncertainty decision node, the scheduler temporarily expands the token budget, spawns parallel search threads, and merges results through validation gates.
Benchmark Results
Evaluated on SWE-bench style long-horizon repository refactoring benchmarks.
Demonstrated Results
Focused inference expenditure proportionally on high-uncertainty decision nodes, increasing task completion rates while lowering aggregate token consumption.
Entropy Overhead
Estimating branch entropy adds a small upfront evaluation step (~15ms) before task execution begins.
Speculative Multi-Branch Scheduling
Integrating speculative execution across multiple candidate branches concurrently on idle edge GPUs.