Happy to join as Associate Editor of ACM Transactions on Evolutionary Learning and Optimization. The journal covers an extremely exciting area at the intersection of Machine Learning and Optimization.

Alistair Benford presenting our runtime analysis of co-evolutionary algorithms on combinatorial games at @GeccoConf He shows that the runtime can be upper bounded in terms of a graph invariant called switchqbility.

Alberto Moraglio and Francisco Chicano giving a @GeccoConf tutorial on Quantum Optimisation.

Exciting library for OCaml developers interested in ML.

Interesting talk by Papadimitrou at the Nash@75 workshop in Oxford today. He proposed an alternative more computationally feasible solution concept for games based on replicator dynamics. However, I think the infinite population approximation is unrealistic for large games.

Congratulations Paul!.

Evolutionary Algorithms continue to make strong impact in AI and machine learning, particularly when combined with LLMs. This latest work by Google Deepmind goes beyond FunSearch.

Objective functions with variable evaluation cost include models evaluated by physical simulation software.

Runtime analysis of evolutionary algorithms counts fitness function evaluations to opt. We introduce cost models where eval costs differ among search points, allowing cost adaptive optimisation: find optimum by exploring cheaper parts of search space.

Luca Manzoni presenting work by Nils Aall Barricelli in the 1950s. Perhaps the first experiments with a coevolutionary algorithm.

Michael Hellwig presenting a tutorial on constraints handling in evolutionary strategies at the #SSCI conference.

Kyrre Glette with colleagues giving a tutorial on evolutionary robotics at the #ssci conference.

Kyrre Glette @kyrre2000 with colleagues giving a tutorial on evolutionary robotics at the #ssci conference.

Learning in games usually assumes small action spaces. This afternoon at #AAAI2025 we give an oral presentation showing that the PDCoEA co-evolutionary algorithm finds the Nash Equilibrium of the game below (2^n actions) in expected poly(n) time. Joint work with @lss1242

A couple of productive days in Sarajevo working on optimisation under uncertainty as part of the ROAR-NET Cost action.

RT @BogdanFilipic: Young researchers and innovators (under the age of 40) working in the field of randomized optimization may now benefit f….

OpenAI at NeurIPS demoing internal reasoning of their o1 model.

I am attending #NeurIPS this week. Please DM if you are interested in chatting about coevolutionary algorithms (nature-inspired, derivative-free algorithms for computing Nash equilibria in games with large strategy spaces) or the intersection of ML and evolutionary computation.

Fully funded PhD scholarship available on Theory of Evolutionary Algorithms within my research group. We do work at the intersection of evolutionary computation, theoretical computer science and AI. Please get in touch with me for further details.

RT @uobcompsci: 🚀 Exciting news! The 2nd UK AI Conference will be on Fri, 22nd Nov at The Exchange, University of Birmingham. AI researche….