A Hyper-intensional Learning Semantics for Inductive Empirical Knowledge
نویسنده
چکیده
This paper presents a new semantics for inductive empirical knowledge. The epistemic agent is represented concretely as a learner who processes new inputs through time and who forms new beliefs from those inputs by means of a concrete, computable learning program. The agent’s belief state is represented hyperintensionally as a set of time-indexed sentences. Knowledge is interpreted as avoidance of error in the limit and as having converged to true belief from the present time onward. Familiar topics are re-examined within the semantics, such as inductive skepticism, the logic of discovery, Duhem’s problem and the articulation of theories by auxiliary hypotheses, the role of serendipity in scientific knowledge, Fitch’s paradox and deductive closure of knowability, whether one can know inductively that one knows inductively, whether one can know inductively that one does not know inductively, and whether expert instruction can spread common inductive knowledge through a community, rather than merely exhibit it.
منابع مشابه
A Computational Learning Semantics for Inductive Empirical Knowledge
This paper presents a new semantics for inductive empirical knowledge. The epistemic agent is represented concretely as a learner who processes new inputs through time and who forms new beliefs from those inputs by means of a concrete, computable learning program. The agent’s belief state is represented hyper-intensionally as a set of time-indexed sentences. Knowledge is interpreted as avoidanc...
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