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import numpy as np | ||
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class Reasoner: | ||
def __init__(self, knowledge_graph): | ||
self.knowledge_graph = knowledge_graph | ||
self.rules = [] # Initialize rules | ||
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def reason(self, knowledge_graph): | ||
# Apply rules to knowledge graph | ||
for rule in self.rules: | ||
rule.apply(knowledge_graph) | ||
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def get_action(self): | ||
# Determine action based on knowledge graph | ||
return np.random.choice(["action1", "action2", "action3"]) | ||
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def learn(self, feedback): | ||
# Update rules based on feedback | ||
pass | ||
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def get_new_knowledge(self): | ||
# Return new knowledge generated by reasoner | ||
return [] | ||
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def __str__(self): | ||
return f"Reasoner(knowledge_graph={self.knowledge_graph}, rules={self.rules})" | ||
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def __repr__(self): | ||
return repr(self.rules) |