Tri-Spirit decomposes autonomous AI into planning, reasoning, and execution layers on heterogeneous hardware, yielding 75.6% lower latency, 71.1% less energy, and 77.6% offline task completion in 2000-task simulations.
Temporal abstraction in reinforcement learning
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Rethinking AI Hardware: A Three-Layer Cognitive Architecture for Autonomous Agents
Tri-Spirit decomposes autonomous AI into planning, reasoning, and execution layers on heterogeneous hardware, yielding 75.6% lower latency, 71.1% less energy, and 77.6% offline task completion in 2000-task simulations.