From the 1 of 4 linked papers with an AI index.
4 papers
SCOPE: Synthetic Conditional Objectives for Policy Evolution in Black-Box Combinatorial Optimization
Nguyen Viet Tuan Kiet, Nguyen Huu Duc, Le Cong Bang +2
The paper proposes SCOPE, a framework that learns synthetic conditional objectives from search history to evolve diverse search policies for black-box combinatorial optimization, i…
RELIC: Revealed Principles for Learning Interpretable Composable Skills in Multi-Agent Planning
Nguyen Viet Tuan Kiet, Bui Dinh Pham, Duong Quoc Chinh +3
Multi-agent planning becomes substantially harder when agents must improve specialized decision-making skills while keeping their executable implementations private. This setting a…
Back to the Beginning of Heuristic Design: Bridging Code and Knowledge with LLMs
Nguyen Viet Tuan Kiet, Bui Dinh Pham, Dao Van Tung +2
Large language models (LLMs) have recently advanced automatic heuristic design (AHD) for combinatorial optimization (CO), where candidate heuristics are iteratively proposed, evalu…
MOTIF: Multi-strategy Optimization via Turn-based Interactive Framework
Nguyen Viet Tuan Kiet, Dao Van Tung, Tran Cong Dao +1
Designing effective algorithmic components remains a fundamental obstacle in tackling NP-hard combinatorial optimization problems (COPs), where solvers often rely on carefully hand…