19 citations · 22 across the 10 of their papers we have counts for
12 papers
Assembling the CREW: A Collaborative Multi-agent Reinforcement Learning Framework for Automated Related Work Generation
Hai-Dang Dang, Bao-Yen Pham, Bao Nguyen +2
Automatic Related Work Generation (RWG) significantly reduces the human time and effort required to author the Related Work Section (RWS) of a research paper. However, prior method…
Probabilistic Focal Search: Accelerating Bounded-Suboptimal Search via Lower-Bound Advancement
Minh Vu Duc, Trung Le Huu, Hà Minh Hoàng +3
Bounded-suboptimal search seeks a solution within a factor of optimal while reducing search effort. Focal Search (FS) uses heuristic guidance within FOCAL, the frontier nodes e…
Diagnose, Recover, Certify: Task Readiness under Hidden Dynamics Changes
Nguyen Viet Tuan Kiet, Huynh Thi Thanh Binh
A deployed control policy can conceal consequential dynamics changes: an actuator may lose effectiveness without affecting the current task when the policy rarely excites it, despi…
SCOPE: Synthetic Conditional Objectives for Policy Evolution in Black-Box Combinatorial Optimization
Nguyen Viet Tuan Kiet, Nguyen Huu Duc, Le Cong Bang +2
Black-box combinatorial optimization requires systematically identifying high-quality solutions under a limited evaluation budget, yet the unknown objective function provides littl…
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…
Zero-shot Quantum Neural Architecture Search
Tung Dao, Son N. Tran, Huynh Thi Thanh Binh
Variational Quantum Algorithms (VQAs) are a leading approach to exploiting near-term quantum hardware, leveraging parameterized quantum circuits and classical optimization to achie…
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…
Pareto-Grid-Guided Large Language Models for Fast and High-Quality Heuristics Design in Multi-Objective Combinatorial Optimization
Minh Hieu Ha, Hung Phan, Tung Duy Doan +3
Multi-objective combinatorial optimization problems (MOCOP) frequently arise in practical applications that require the simultaneous optimization of conflicting objectives. Althoug…
Minimizing the energy depletion in wireless rechargeable sensor networks using bi-level metaheuristic charging schemes
Huynh Thi Thanh Binh, Le Van Cuong, Dang Hai Dang +1
Recently, Wireless Rechargeable Sensor Networks (WRSNs) that leveraged the advantage of wireless energy transfer technology have opened a promising opportunity in solving the limit…
HSEvo: Elevating Automatic Heuristic Design with Diversity-Driven Harmony Search and Genetic Algorithm Using LLMs
Pham Vu Tuan Dat, Long Doan, Huynh Thi Thanh Binh
Automatic Heuristic Design (AHD) is an active research area due to its utility in solving complex search and NP-hard combinatorial optimization problems in the real world. The rece…
Phase Shift Design for RIS-Aided Cell-Free Massive MIMO with Improved Differential Evolution
Trinh Van Chien, Cuong V. Le, Huynh Thi Thanh Binh +2
This paper proposes a novel phase shift design for cell-free massive multiple-input and multiple-output (MIMO) systems assisted by reconfigurable intelligent surface (RIS), which o…
Joint Transaction Transmission and Channel Selection in Cognitive Radio Based Blockchain Networks: A Deep Reinforcement Learning Approach
Nguyen Cong Luong, Tran The Anh, Huynh Thi Thanh Binh +3
To ensure that the data aggregation, data storage, and data processing are all performed in a decentralized but trusted manner, we propose to use the blockchain with the mining poo…