Memetic algorithm

Related lectures (28)

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Explores optimization in neuron modeling, addressing underconstrained parameters, fitness functions, and successful fitting of firing patterns.

Explores optimization-driven design, differentiable simulation, control strategies, and the evolution of virtual creatures and soft machines.

Delves into Pareto optimization techniques for generating system configurations and making decisions efficiently.

Covers the application of the two-phase Simplex algorithm to solve linear programming problems.

Explores simulated annealing for optimization, emphasizing parameter tuning and diversification to escape local minima.

Explores Markov chains and algorithm applications, including exact simulation and Propp-Wilson algorithms.

Explores the application of deep generative models in drug discovery, focusing on designing small molecules and optimizing molecular structures.

Covers Markov chains and their applications in algorithms, focusing on Markov Chain Monte Carlo sampling and the Metropolis-Hastings algorithm.

Explores Cheeger's inequalities for random walks on graphs and their implications.

Explores universality, consensus objects, shared memory models, and FIFO Queue implementation.