24 papers · ranked by Valyu relevance
Frank Hutter, Holger H. Hoos, Kevin Leyton‐Brown, T. Stuetzle
The identification of performance-optimizing parameter settings is an important part of the development and application of algorithms. We describe an automatic framework for this algorithm configuration problem. More formally, we provide methods for optimizing a target algorithm's performance on a given class of…
Maxime Bouscary, Manxi Wu, Saurabh Amin
Large language models (LLMs) have emerged as powerful tools for automatic algorithm design (AAD). However, existing pipelines remain inefficient. They operate at the granularity of full algorithms, redundantly rewriting recurring substructures and discarding low-fitness candidates that may contain valuable algorithmic…
Yanan Sun, Bing Xue, Mengjie Zhang, Gary G. Yen + 1 more
—Convolutional Neural Networks (CNNs) have gained a remarkable success on many image classification tasks in recent years. However, the performance of CNNs highly relies upon their architectures. For most state-of-the-art CNNs, their architectures are often manually-designed with expertise in both CNNs and the…
Jin Huang, Xinyu Li, Liang Gao, Qihao Liu + 1 more
self-evolution for dynamic job shop scheduling problem Authors: ['Jin Huang' 'Xinyu Li' 'Liang Gao' 'Qihao Liu' 'Yue Teng'] Abstract—Heuristic dispatching rules (HDRs) are widely regarded as effective methods for solving dynamic job shop scheduling problems (DJSSP) in real-world production environments. However, their…
Pham Vu Tuan Dat, L. Doan, Huynh Thi Thanh Binh
Harmony Search and Genetic Algorithm Using LLMs Authors: ['Pham Vu Tuan Dat' 'L. 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 recent advancements in Large…
Jonas Kuckling
Swarm robotics is a promising approach to control large groups of robots. However, designing the individual behavior of the robots so that a desired collective behavior emerges is still a major challenge. In recent years, many advances in the automatic design of control software for robot swarms have been made, thus…
Mauro Birattari, Antoine Ligot, Darko Bozhinoski, Manuele Brambilla + 10 more
'Gianpiero Francesca' 'Lorenzo Garattoni' 'David Garzón Ramos' 'Ken Hasselmann' 'Miquel Kegeleirs' 'Jonas Kuckling' 'Federico Pagnozzi' 'Andrea Roli' 'Muhammad Salman' 'Thomas Stützle'] Designing collective behaviors for robot swarms is a difficult endeavor due to their fully distributed, highly redundant, and…
Jonas Kuckling, Thomas Stützle, Mauro Birattari, José Manuel Galán
Iterative improvement is an optimization technique that finds frequent application in heuristic optimization, but, to the best of our knowledge, has not yet been adopted in the automatic design of control software for robots. In this work, we investigate iterative improvement in the context of the automatic modular…
Jan Mendling, Benoît Depaire, Henrik Leopold
There is an ongoing debate in computer science how algorithms should best be studied. Some scholars have argued that experimental evaluations should be conducted, others emphasize the benefits of formal analysis. We believe that this debate less of a question of either-or, because both views can be integrated into an…
Antoine Ligot, Jonas Kuckling, Darko Bozhinoski, Mauro Birattari + 1 more
'Robertas Damaševičius'] We investigate the possibilities, challenges, and limitations that arise from the use of behavior trees in the context of the automatic modular design of collective behaviors in swarm robotics. To do so, we introduce Maple, an automatic design method that combines predefined modules-low-level…
Qi Zhang, Chang Liu, Stephen Wu, Ryo Yoshida
In the last few years, de novo molecular design using machine learning has made great technical progress but its practical deployment has not been as successful. This is mostly owing to the cost and technical difficulty of synthesizing such computationally designed molecules. To overcome such barriers, various methods…
Kathleen S. Dreyer, Anh V. Nguyen, Gauri G. Bora, Lauren E. Redus + 6 more
Genetic programs can direct living systems to perform diverse, pre-specified functions. As the library of parts available for building such programs continues to expand, computation-guided design is increasingly helpful and necessary. Predictive models aid the challenging design process, but iterative simulation and…
Reza Mousavi, Daniel Lobo
Synthetic developmental biology aims to engineer gene regulatory mechanisms (GRMs) for understanding and producing desired multicellular patterns and shapes. However, designing GRMs for spatial patterns is a current challenge due to the nonlinear interactions and feedback loops in genetic circuits. Here we present a…
Mehran Afshari, Behrooz Arezoo
One of the most challenging topics in progressive die design is strip layout design. In the present study, a new method is presented for the automatic strip layout design for progressive dies using the Grouping Genetic Algorithm. A two-objective function is used in the optimization process. The first objective is…
Frederick Starkey, Filippo Menolascina
Synthetic Biology aims to rationally engineer biological systems. Current methods often employ an initial human designed circuit topology and utilise iterative approaches, e.g. directed evolution, to fine-tune part function. This approach can be extremely time consuming and resource intensive whilst often reaching…
Bruno Tardiole Kuehne, Julio Cezar Estrella, Luiz Henrique Nunes, Edvard Martins de Oliveira + 6 more
'Edvard Martins de Oliveira' 'Luis Hideo Nakamura' 'Carlos Henrique Gomes Ferreira' 'Regina Helena Carlucci Santana' 'Stephan Reiff-Marganiec' 'Marcos José Santana' 'Muhammad Khurram Khan'] This paper proposes a system named AWSCS (Automatic Web Service Composition System) to evaluate different approaches for automatic…
Authors not listed
Bridging AI and self-driving laboratories, we introduce the first fully-automated, closed-loop molecular discovery cycle, exemplified by the identification of novel JAK inhibitors. With minimal human intervention, we combined AI-driven molecular design and retrosynthesis with IBM’s synthesis automation system RoboRXN…
Anh Phong Tran, Dhruv D. Jatkar, M. Ali Al-Radhawi, Elizabeth A. Ernst + 1 more
Minimal synthesis of Boolean functions is an NP-hard problem, and heuristic approaches typically give suboptimal circuits. However, in the emergent field of synthetic biology, genetic logic designs that use even a single additional Boolean gate can render a circuit unimplementable in a cell. This has led to a renewed…
Authors not listed
Chemical reactions are regarded as transformations of chemical structures, and the question of which atoms in the reactants correspond to which atoms in the products has attracted chemists for a long time. Atom-to-atom mapping (AAM) is a procedure that establishes such correspondence(s) between the atoms of reactants…
Iiris Sundin, Alexey Voronov, Haoping Xiao, Kostas Papadopoulos + 5 more
A de novo molecular design workflow can be used together with technologies such as reinforcement learning to navigate the chemical space. A bottleneck in the workflow that remains to be solved is how to integrate human feedback in the exploration of the chemical space to optimize molecules. A human drug designer still…
Authors not listed
More sustainable chemical processes require the selection of suitable molecules, which can be supported by computer-aided molecular design (CAMD). CAMD often generates and evaluates molecular structures using genetic algorithms. However, genetic algorithms can suffer from slow convergence, and might yield suboptimal…
Authors not listed
This comprehensive review examines the evolution of autonomous materials synthesis laboratories that integrate artificial intelligence with advanced robotics to accelerate discovery. Traditional materials development pipelines typically require 10-20 years, but self-driving laboratories (SDLs) and Materials…
Miguel Á. Valderrama-Gómez, Jason G. Lomnitz, Rick A. Fasani, Michael A. Savageau
Mechanistic models of biochemical systems provide a rigorous kinetics-based description of various biological phenomena. They are indispensable to elucidate biological design principles and to devise and engineer systems with novel functionalities. To date, mathematical analysis and characterization of these models…
Wenyu Zhang, Mason Guy, Jerrica Yang, Lucy Hao + 5 more
Large Language Models (LLMs) have revolutionized numerous industries as well as accelerated scientific research. However, their application in planning and conducting experimental science, has been limited. In this study, we introduce an adaptable prompt-set with GPT-4, converting literature experimental procedures…