صورت‌بندي گرايش‌هاي گزاره‌اي در منطق و هوش‌مصنوعي با تاكيد بر منطق‌هاي BDI و KARO

Formalizing propositional attitudes in logic an‎d artificial intelligence with a focus on the logics BDI an‎d KARO

فلسفه

With the advancement of artificial intelligence (AI) an‎d the proliferation of agent-based intelligent systems, the formalization of propositional attitudes—such as belief, knowledge, desire, an‎d intention—has gained paramount importance. These formalizations enable more precise modeling of human-like behaviors in machines, which is essential for applications including robotics, autonomous decision-making, an‎d ethical AI systems. Without such rigorous formal frameworks, AI may prove inefficient in comprehending an‎d predicting mental states, potentially leading to critical errors in human-machine interactions. Therefore, this thesis focuses on the examination an‎d formalization of these attitudes within logic an‎d AI, bridging the gap between philosophy of mind an‎d emerging technologies. This thesis analyzes propositional attitudes across categories such as cognitive, conative, informational, normative, an‎d motivational, an‎d formalizes them within epistemic logic, deontic logic, BDI logic (belief-desire-intention, based on CTL* temporal logic), an‎d the KARO framework (knowledge, abilities, results, an‎d opportunities, based on dynamic logic). The formalization of these logics is specifically investigated in the context of AI, employing possible worlds semantics an‎d computational models to demonstrate that these frameworks are not only theoretically valuable but also practically applicable in designing autonomous an‎d intelligence agents. Ultimately, the thesis proposes integrating these frameworks for modeling agentsʹ internal norms, thereby laying the groundwork for future AI research.

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