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  1. The algorithmic mind [electronic resource] : a study of inference in action

    Icard, Thomas F., III.

    What is the nature of human inference? How does it work, why does it work that way, and how might we like it to work? I advance a framework for answering these questions in tandem, with a rich interplay between normative and descriptive considerations. Specifically, I explore a view of inference based on the idea of probabilistic sampling, which is supported by behavioral psychological data and appears to be neurally plausible, and which also engenders a philosophically novel and appealing view of subjective probability. I then discuss this view in the context of the Bayesian program in cognitive psychology, proposing a methodology of boundedly rational analysis, which particularly exemplifies the normative/descriptive interplay. By taking resource bounds seriously, we can improve and augment the more standard rational analysis strategy. This helps us focus efforts to understand how minds in fact infer, and in turn allows sharpening normative questions about how minds ought to infer. Against this background I explore the phenomenon of metareasoning, which arises naturally when discussing bounded but representationally sophisticated agents, but which has not been explored in the context of probabilistic approaches to the mind. I propose an analysis of metareasoning in terms of the value of information, and explore the consequences of this view for how we should think about inference. The focus of this dissertation is on implemented (or at least implementable) models of agents, and the role of inference in guiding and supporting intelligent action for real, resource-bounded agents. Consequently, a number of the suggestions and claims made are supported by simulation studies.

  2. Logic, rationality, and interaction : 8th International Workshop, LORI 2021, Xi'ian, China, October 16-18, 2021, Proceedings

    Cham, Switzerland : Springer, 2021.

    This LNCS book is part of the FOLLI book series and constitutes the proceedings of the 8th International Workshop on Logic, Rationality, and Interaction, LORI 2021, held in Xi`an, China, in October 2021. The 15 full papers presented together with 7 short papers in this book were carefully reviewed and selected from 40 submissions. The workshop covers a wide range on the following topics such as doxastic and epistemic logics, deontic logic, intuitionistic and subsstructural logics, voting theory, and (a new theme emphasized this year) causal inference.

    Online SpringerLink

  3. Assessing Measures of Explanatory Power

    Beasley, Jack
    June 4, 2021

    Measures of explanatory power have a key point of discussion recently in the context of epistemic research into abduction or inference to the best explanation. Many recent works have integrated explanatory power into Bayesian inference rules, arguing that such inference rules converge more quickly or are otherwise better than inference using Bayes' rule. This thesis proposes a pragmatic test, explanation task superiority, which attempts to determine if belief inference rules capture more or less valuable information than one another. This test borrows the decision theory literature's partially-observable Markov decision process (POMDP) formulation to separate epistemic and pragmatic rationality to assess a belief update rule by the value of its epistemic rationality. Through simulation, the thesis then shows that currently proposed inference rules which incorporate explanatory power fail to capture valuable information that inference by Bayes' rule does not and thus are not explanation task superior.


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