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PromptLogic.txt
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PromptLogic.txt
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Prompt Optimization with Logic-Driven GA and DE
### Pseudo-Code for EvoPrompt Optimization with Logic-Driven GA and DE
#### Common Initialization (Init)
```pseudo
Init:
Population = GenerateInitialPrompts()
EvaluateFitness(Population)
```
#### Genetic Algorithm (GA) Approach
```pseudo
GA_Optimization:
WHILE NOT TerminationCondition() DO
Selected = SelectPrompts(Population, LogicBasedCriteria)
Offspring = Crossover(Selected, LogicalCombination)
Mutated = Mutate(Offspring, ContextualAlteration)
Population = Replace(Population, Mutated)
EvaluateFitness(Population)
END WHILE
Return BestPrompt(Population)
```
#### Differential Evolution (DE) Approach
```pseudo
DE_Optimization:
WHILE NOT TerminationCondition() DO
FOR EACH prompt IN Population DO
Mutant = MutatePrompt(prompt, LogicalAlteration)
Trial = Crossover(prompt, Mutant)
IF Fitness(Trial) > Fitness(prompt) THEN
Replace(prompt, Trial)
END IF
END FOR
EvaluateFitness(Population)
END WHILE
Return BestPrompt(Population)
```
#### Supporting Functions
```pseudo
GenerateInitialPrompts: Create initial set of prompts using task-specific logic
EvaluateFitness: Assess each prompt based on effectiveness and logic alignment
SelectPrompts: Choose prompts for crossover based on performance and diversity
Crossover: Combine elements of prompts while maintaining logical coherence
Mutate: Introduce logical changes to prompts to explore new possibilities
Replace: Update population with new or mutated prompts
TerminationCondition: Check if the optimization goal is met or max iterations reached
BestPrompt: Select the prompt with the highest fitness score
```