Topological Semantics for Common Inductive Knowledge
This work addresses the foundational problem of multi-agent coordination under inductive uncertainty, relevant to epistemology and distributed decision-making.
The paper introduces a logic for solving 'inductive coordinated attack,' where scientists with private experiments must converge on a hypothesis without communication, avoiding false positives. It provides a topological semantics based on agents' inductive standards and shows soundness, demonstrating how hypotheses can become common inductive knowledge.
Consider a community of scientists whose labs are each capable of conducting a different set of experiments. The scientists want to work together to confirm a new hypothesis, but to ensure blindness, their labs generally prohibit the scientists from communicating with each other. Further, each scientist can only make so many retractions to their lab before having to cease inquiry and suspend judgement forever. How might the scientists coordinate whether to affirm or suspend judgement on this hypothesis in light of their private experiments so that their labs are guaranteed to converge to the same conclusion and that this conclusion will not be a false positive? Call this problem 'inductive coordinated attack.' In this paper, we develop a logic for solving inductive coordinated attack by determining when and how a hypothesis can become what we call 'common inductive knowledge.' We begin by precisifying Lewis' account of common knowledge in Convention which describes the generation of higher-order expectations between agents as hinging upon agents' inductive standards and a shared witness. Our language has a rather rich syntax in order to capture equally rich notions central to Lewis' account; for instance, we speak of an agent 'having inductive reason to believe' a proposition and one proposition 'indicating' to an agent that another proposition holds. This syntax affords a novel topological semantics which, following Kelly 1996's approach in The Logic of Reliable Inquiry, takes as primitives agents' information bases. In particular, we endow each agent with a 'switching tolerance' meant to represent their personal inductive standards for learning. After establishing soundness of our proof system with respect to this semantics, we conclude by showing how our logic can be used to solve inductive coordinated attack.