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BEGIN:VEVENT
DTSTAMP:20260402T024534Z
LOCATION:Level 2 Lobby
DTSTART;TZID=America/Los_Angeles:20250623T180000
DTEND;TZID=America/Los_Angeles:20250623T190000
UID:dac_DAC 2025_sess262_RESEARCH2578@linklings.com
SUMMARY:Self-Motivated Agents for Analog Circuit Optimization via Intrinsi
 c Reward
DESCRIPTION:Sumin Oh and HyunJin Kim (Dankook University)\n\nAnalog circui
 t optimization remains challenging due to its high-dimensional design spac
 e and the prohibitive cost of SPICE simulations. To improve sample efficie
 ncy, we propose an RL framework that uses intrinsic rewards, enabling agen
 ts to explore novel circuit regions. Furthermore, by leveraging an autoenc
 oder-based novelty estimator, our approach enhances exploration and accele
 rates convergence, outperforming conventional methods. Experimental result
 s on practical circuits demonstrate significant performance improvements o
 ver baselines.\n\nTracks: DES5: Emerging Device and Interconnect Technolog
 ies\n\n
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