PulseAugur
EN
LIVE 14:00:25

LLM framework OccuReward enhances demographic equity in building energy management

Researchers have developed OccuReward, a framework that uses LLMs to shape reward functions for energy management in grid-interactive buildings, aiming to improve demographic equity. The system utilizes the Gemini API to iteratively refine reward logic and weights, focusing on occupant comfort. Initial results showed elderly females experienced the lowest satisfaction, but after three rounds of refinement, satisfaction improved significantly across various demographic groups while also reducing energy costs. AI

IMPACT This research demonstrates how LLMs can be leveraged to improve fairness and occupant comfort in AI-driven building systems, potentially influencing future smart building designs.

RANK_REASON The cluster is based on an academic paper introducing a new framework and methodology for LLM-guided reward shaping in building energy management. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Shadmehr Zaregarizi, Khashayar Yavari ·

    OccuReward: LLM-Guided Occupant-Centric Reward Shaping for Demographic Equity in Grid-Interactive Buildings

    arXiv:2605.28168v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated promising capability in generating reward functions for deep reinforcement learning (DRL)-based building energy management. However, their potential to exhibit or exacerbate disparities…