genetic algorithms
Genetic algorithms are a type of computer algorithm that uses concepts from evolutionary biology to solve complex problems by mimicking the process of natural selection, mutation, and reproduction. The algorithms generate a population of potential solutions that are evaluated based on a fitness function and then iteratively evolve through the selection and recombination of genetic information to create new generations of potential solutions until an optimal solution is found.
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Related Concepts (41)
- adaptive systems
- artifical intelligence
- artificial intelligence
- artificial intelligence and robotics
- binary code mutation
- chromosome
- chromosomes
- complexity
- computational intelligence
- convergence
- convergence analysis
- convergent instrumental goals
- crossover operator
- decision-making algorithms
- diversity maintenance
- evolutionary algorithms
- evolutionary computation
- fitness function
- fitness landscape
- genetic diversity
- genetic evolution
- genetic operators
- genetic programming
- genetic representation
- genetic variation
- intelligent systems
- machine learning
- mutation operator
- natural selection
- niche formation
- optimization
- optimization problems
- pattern formation
- population
- population dynamics
- rapid autonomous development
- selection operator
- selection strategies
- stochastic prediction
- superintelligence
- swarm intelligence
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- algorithms
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- cellular automata and genetic algorithms for pattern recognition
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- genetic algorithms and cellular automata in artificial life research
- geneticists
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- randomized algorithms
- robotics algorithms
- training algorithms