43 lines
1.3 KiB
Python
43 lines
1.3 KiB
Python
from algorithm.state import State
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from .gene import *
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from .genome import initialize_genomes
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class NEAT:
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def __init__(self, config):
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self.config = config
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if self.config['gene_type'] == 'normal':
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self.gene_type = NormalGene
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else:
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raise NotImplementedError
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def setup(self, randkey):
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state = State(
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randkey=randkey,
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P=self.config['pop_size'],
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N=self.config['maximum_nodes'],
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C=self.config['maximum_connections'],
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S=self.config['maximum_species'],
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NL=1 + len(self.gene_type.node_attrs), # node length = (key) + attributes
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CL=3 + len(self.gene_type.conn_attrs), # conn length = (in, out, key) + attributes
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input_idx=self.config['input_idx'],
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output_idx=self.config['output_idx']
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)
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pop_nodes, pop_conns = initialize_genomes(state, self.gene_type)
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next_node_key = max(*state.input_idx, *state.output_idx) + 2
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state = state.update(
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pop_nodes=pop_nodes,
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pop_conns=pop_conns,
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next_node_key=next_node_key
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)
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return state
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def tell(self, state, fitness):
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return State()
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def ask(self, state):
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return State()
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