Large Language Models for and with Evolutionary Computation (LLMfwEC) 

Workshop at GECCO 2024, July 14-18th, 2024, Melbourne, Australia

Home

Overview and Scope

Large language models (LLMs), along with other Foundational Models (generative AI methods), have disrupted conventional expectations of Artificial Intelligence and Machine Learning systems. An LLM processes natural language text prompts as input and responds with the resulting pattern matching and sequence completion with output in natural language text. In contrast, Evolutionary Computation(EC) is inspired by Neo-Darwinian evolution and they conduct black-box search and optimization. What brings these two approaches together? 

One answer is evolutionary search heuristics, with operators that use LLMs to fulfill their function. This hybridization turns the conventional paradigm that ECs use on its head, and in turn, sometimes yields high performing, and novel EC systems. 

Another answer is using LLM for EC. Many fields have experienced significant growth, with numerous nature-inspired algorithms being developed to solve complex problems. EC has become the target or source of many hybrid approaches and analyses, combinations of the advantages of multiple algorithms, the introduction of adaptive techniques that improve their performance, and special tools. LLMs may help researchers in the selection of feasible candidates from the pool of algorithms based on user- specified goals and provide a basic description of the methods, or propose novel hybrid methods. Further, the models can help identify and describe distinct components suitable for adaptive enhancement, or hybridization, and finally provide a pseudo-code, implementation, and reasoning for the proposed methodology.

This workshop calls for papers at the intersection of EC and LLMs, an area we call "EC with LLM" and "LLM for EC". We invite original research papers discussing  from the connection between LLMs and EC.  This workshop is focused on algorithms that were developed on a solid foundation of theory, analyses, evidence, well defined balancing between exploration and exploitation like Genetic Algorithms (GA), Genetic Programming (GP), Evolution Strategies (ES), Differential Evolution (DE), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and more.

Topics of Interest  

It includes(but is not restricted to the following topics):

Submissions

We invite submissions of the following types of papers:

Accepted submissions will be presented during the workshop and will appear in the GECCO Companion ACM proceedings. Paper's format should follow the GECCO 2024 instructions. 

Submissions of early and in-progress work are encouraged. Authors of accepted papers proposing novel software developments will be encouraged to give a demo or a short introductory tutorial. Authors of accepted papers describing novel software or technical developments will be encouraged to give a demonstration during the workshop. 

Instructions

Important Dates

Organizers

Schedule

Preliminary:

○       [5 min.] Welcome & Opening by the workshop organizers

○       [15 min.] LLM Fault Localisation within Evolutionary Computation Based Automated Program Repair; Bin Murtaza, McCoy, Ren, Murphy, Banzhaf

○       [15 min.] Comparing Large Language Models and Grammatical Evolution for Code Generation; Custode, Migliore Rambaldi, Roveri, Iacca

○       [15 min.] L-AutoDA: Large Language Models for Automatically Evolving Decision-based Adversarial Attacks; Guo, Liu, Lin, Zhao, Zhang

○       [15 min.] An investigation on the use of Large Language Models for hyperparameter tuning in Evolutionary Algorithms; Custode, Caraffini, Yaman, Iacca

○       [15 min.] A Critical Examination of Large Language Model Capabilities in Iteratively Refining Differential Evolution Algorithm; Pluhacek, Kovac, Janku, Kadavy, Senkerik, Viktorin

○       [25 min.] Panel discussion. Panelists: Una-May O’Reilly and TBC 

○       [5 min.] Goodbye & Closing by the workshop organizers


Contact

Send an email to hembergerik@csail.mit.edu including "LLMfwEC-2024" in the subject