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evolutionary computation

topic3 events
papersTODAY 04:00 UTC

Surrogate-Assisted Genetic Programming with Phenotypic Characterisation for Dynamic Scheduling

A new arXiv paper applies genetic programming to dynamic multi-mode resource-constrained project scheduling, where tasks face precedence rules, limited resources, several execution modes, and uncertain durations. The authors add surrogate assistance and phenotypic characterisation to guide the evolutionary search toward promising schedules. The work sits at the intersection of evolutionary computation and operations research rather than commercial AI products.

genetic-programming/scheduling/optimization/research
papersTODAY 04:00 UTC

arXiv paper proposes evolutionary framework for multi-agent Q-learning with mean-field feedback

A new arXiv preprint introduces an evolutionary computation approach to multi-agent reinforcement learning in networked populations. The framework combines individual adaptation, local interactions, and shifting environmental conditions through mean-field environmental feedback. The authors frame the work as a way to study how these coupled learning and environment dynamics interact.

multi-agent/reinforcement-learning/research/evolutionary-computation
papersSEP 10 04:00 UTC

Genetic Algorithm Approach to Bayesian Network Fusion Under Treewidth Limits

A new arXiv paper proposes using evolutionary computation to merge several Bayesian networks into a single consensus structure. The method treats fusion as an optimization problem, seeking a combined network that preserves key dependencies from each input while keeping treewidth bounded for computational tractability.

bayesian-networks/genetic-algorithms/probabilistic-models/structure-learning