aimwhether

aimwhether is a neologism used in discussions of decision-making and artificial intelligence to describe a framework that combines goal-oriented planning with explicit consideration of conditional truths. The term blends "aim" and "whether" to signal two coordinating aspects of reasoning: (1) the agent's goals and desired end states, and (2) the evaluation of propositions that may hold across possible worlds or outcomes. In practice, an aimwhether approach guides action selection by modeling both goal attainment likelihoods and the truth-values of key conditions that affect outcomes.

Etymology and usage: The coinage emerged in online philosophy and AI blogs in the late 2010s as a descriptive label for methods that pair goal-directed reasoning with conditional analysis. It has not achieved wide scholarly adoption, and its definitions vary between sources.

Concept and applications: In AI planning, aimwhether refers to algorithms that simultaneously optimize for goal satisfaction while verifying conditional constraints (safety, feasibility) under uncertainty. In cognitive science, it describes a metacognitive strategy in which agents assess both what they want (aim) and which propositions about the environment are true (whether) to select strategies. Examples include robust planning under partial observability and policy evaluation across alternative worlds.

Relationship to related concepts: It overlaps with conditional planning, goal-conditioned reasoning, and metacognitive decision strategies. It differs from simple goal pursuit by foregrounding the explicit evaluation of conditionals as a structured step in reasoning.

Limitations: As a niche term, it lacks formal consensus and precise formalization, and may be confused with generic phrases about evaluating whether actions achieve goals.