I can tell you know a lot, although I'm not sure what: Modeling broad epistemic inference from minimal action

Inferences about other people's knowledge and beliefs are central to social interaction. In many situations, however, it's not possible to be sure what other people know because their behavior is consistent with a range of potential epistemic states. Nonetheless, this behavior can give us coarse intuitions about how much someone might know, even if we cannot pinpoint the exact nature of this knowledge. We present a computational model of this kind of broad epistemic-state inference, centered on the expectation that agents maximize epistemic utilities. We evaluate our model in a graded inference task where people had to infer how much an agent knew based on the actions they chose. Critically, the agent's behavior was always under-determined, but nonetheless contained information about how much knowledge they possessed. Our model captures nuanced patterns in participant judgments, revealing a quantitative capacity to infer amorphous knowledge from minimal behavioral evidence.

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Comparative standard in institutional epistemology

Filozofija i drustvo ◽

10.2298/fid1903418z ◽

2019 ◽

Vol 30 (3) ◽

pp. 418-430

Author(s):

Marko-Luka Zubcic

Keyword(s):

Institutional Arrangements ◽

Moral Conflict ◽

Epistemic Value ◽

Epistemic State ◽

Epistemic States ◽

The Social ◽

Democratic Authority ◽

Philosophical Framework ◽

Lock In ◽

Agent Development

Which epistemic value is the standard according to which we ought to compare, assess and design institutional arrangements in terms of their epistemic properties? Two main options are agent development (in terms of individual epistemic virtues or capabilities) and attainment of truth. The options are presented through two authoritative contemporary accounts-agent development by Robert Talisse?s understanding in Democracy and Moral Conflict (2009) and attainment of truth by David Estlund?s treatment, most prominently in Democratic Authority: A Philosophical Framework (2008). Both options are shown to be unsatisfactory because they are subject to problematic risk of suboptimal epistemic state lock-in. The ability of the social epistemic system to revise suboptimal epistemic states is argued to be the best option for a comparative standard in institutional epistemology.

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Managing Different Sources of Uncertainty in a BDI Framework in a Principled Way with Tractable Fragments

Journal of Artificial Intelligence Research ◽

10.1613/jair.5287 ◽

2017 ◽

Vol 58 ◽

pp. 731-775

Author(s):

Kim Bauters ◽

Kevin McAreavey ◽

Weiru Liu ◽

Jun Hong ◽

Lluís Godo ◽

...

Keyword(s):

Intelligent Systems ◽

Large Scale ◽

Operational Semantics ◽

Epistemic State ◽

Bdi Agents ◽

Epistemic States ◽

Interacting Agents ◽

Different Types ◽

Syntactic Approach ◽

Different Sources

The Belief-Desire-Intention (BDI) architecture is a practical approach for modelling large-scale intelligent systems. In the BDI setting, a complex system is represented as a network of interacting agents - or components - each one modelled based on its beliefs, desires and intentions. However, current BDI implementations are not well-suited for modelling more realistic intelligent systems which operate in environments pervaded by different types of uncertainty. Furthermore, existing approaches for dealing with uncertainty typically do not offer syntactical or tractable ways of reasoning about uncertainty. This complicates their integration with BDI implementations, which heavily rely on fast and reactive decisions. In this paper, we advance the state-of-the-art w.r.t. handling different types of uncertainty in BDI agents. The contributions of this paper are, first, a new way of modelling the beliefs of an agent as a set of epistemic states. Each epistemic state can use a distinct underlying uncertainty theory and revision strategy, and commensurability between epistemic states is achieved through a stratification approach. Second, we present a novel syntactic approach to revising beliefs given unreliable input. We prove that this syntactic approach agrees with the semantic definition, and we identify expressive fragments that are particularly useful for resource-bounded agents. Third, we introduce full operational semantics that extend CAN, a popular semantics for BDI, to establish how reasoning about uncertainty can be tightly integrated into the BDI framework. Fourth, we provide comprehensive experimental results to highlight the usefulness and feasibility of our approach, and explain how the generic epistemic state can be instantiated into various representations.

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Changing Minds ― Epistemic Interventions in Causal Reasoning

10.31234/osf.io/db6ms ◽

2021 ◽

Author(s):

Lara Kirfel ◽

David Lagnado

Keyword(s):

Allergic Reaction ◽

Causal Reasoning ◽

Epistemic State ◽

Counterfactual Reasoning ◽

Epistemic States ◽

Epistemic Actions ◽

Causal Action ◽

Epistemic Context ◽

Future Outcomes ◽

Causal Cognition

Did Tom’s use of nuts in the dish cause Billy’s allergic reaction? According to counterfactual theories of causation, an agent is judged a cause to the extent that their action made a difference to the outcome (Gerstenberg, Goodman, Lagnado, & Tenenbaum, 2020; Gerstenberg, Halpern, & Tenenbaum, 2015; Halpern, 2016; Hitchcock & Knobe, 2009). In this paper, we argue for the integration of epistemic states into current counterfactual accounts of causation. In the case of ignorant causal agents, we demonstrate that people’s counterfactual reasoning primarily targets the agent’s epistemic state – what the agent doesn’t know –, and their epistemic actions – what they could have done to know – rather than the agent’s actual causal action. In four experiments, we show that people’s causal judgment as well as their reasoning about alternatives is sensitive to the epistemic conditions of a causal agent: Knowledge vs. ignorance (Experiment 1), self-caused vs. externally caused ignorance (Experiment 2), the number of epistemic actions (Experiment 3), and the epistemic context (Experiment 4). We see two advantages in integrating epistemic states into causal models and counterfactual frameworks. First, assuming the intervention on indirect, epistemic causes might allow us to explain why people attribute decreased causality to ignorant vs. knowing causal agents. Moreover, causal agents’ epistemic states pick out those factors that can be controlled or manipulated in order to achieve desirable future outcomes, reflecting the forward-looking dimension of causality. We discuss our findings in the broader context of moral and causal cognition.

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Evidence of Evidence as Higher-Order Evidence

Higher-Order Evidence ◽

10.1093/oso/9780198829775.003.0003 ◽

2019 ◽

pp. 62-83

Author(s):

Anna-Maria A. Eder ◽

Peter Brössel

Keyword(s):

Everyday Life ◽

Higher Order ◽

Epistemic State ◽

Specific Kind ◽

Epistemic States ◽

Model Evidence ◽

New Evidence ◽

Higher Order Evidence

In everyday life and in science we acquire evidence of evidence and based on this new evidence we often change our epistemic states. An assumption underlying such practice is that the following EEE Slogan is correct: ‘evidence of evidence is evidence’. We suggest that evidence of evidence is best understood as higher-order evidence about the epistemic state of agents. In order to model evidence of evidence the chapter introduces a new powerful framework for modelling epistemic states, Dyadic Bayesianism. Based on this framework, it then discusses characterizations of evidence of evidence and argues for one of them. Finally, the chapter shows that whether the EEE Slogan holds, depends on the specific kind of evidence of evidence.

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From empathy to mirror neurons and back to aesthetics

10.1093/med/9780190060954.003.0005 ◽

2021 ◽

pp. 287-358

Author(s):

Michael A. Arbib

Keyword(s):

Synaptic Plasticity ◽

Reinforcement Learning ◽

Social Interaction ◽

Computational Model ◽

Mirror Neurons ◽

Mirror Neuron ◽

Aesthetic Appreciation ◽

Future Design ◽

Motor Component

This chapter approaches aesthetics anew by considering empathy and Einfühlung, “feeling ourselves into” a work of art or architecture. The key neuroscience is the discovery of mirror neurons in monkeys that inspired the discovery of mirror systems in humans. Unsupervised, supervised, and reinforcement learning, each based on a different rule for synaptic plasticity, are presented as background for a computational model of how mirror neuron wiring is learned. Mirror neurons may serve social interaction, but they also self-monitor in acquiring new behaviors. This is exemplified in modeling how adaptive sequences of behavior may be mastered through learning the desirability and executability of actions. Such opportunistic scheduling complements the role of scripts. Empathy is linked to mirror systems but also depends on systems beyond the mirror. Returning to Einfühlung, we explore how a motor component may enrich our aesthetic appreciation by recognizing the actions and emotions of protagonists in a representational painting, or by gaining some feeling for the actions of the artist, sculptor, or architect in creating the work. Finally, case studies are sampled, including those in neuroaesthetics seeking neural correlates for aesthetic appreciation, that contribute to a tool kit for assessing the experience of buildings to enrich future design.

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Causal judgments about atypical actions are influenced by agents’ epistemic states

10.31234/osf.io/yvstb ◽

2020 ◽

Author(s):

Lara Kirfel ◽

David Lagnado

Keyword(s):

Mental States ◽

Epistemic State ◽

Bayesian Network Model ◽

Abnormal Behaviour ◽

Epistemic States ◽

Causal Judgments ◽

Causal Action ◽

Acting Agent ◽

Epistemic Asymmetry ◽

Causal Cognition

A prominent finding in causal cognition research is people's tendency to attribute increased causality to atypical actions. If two agents jointly cause an outcome ("conjunctive causation’"), but differ in how frequently they have performed the causal action before, people judge the atypically acting agent to have caused the outcome to a greater extent than the normally acting agent. In this paper, we argue that it is the epistemic state of an abnormally acting agent, rather than the abnormality of their action, that is driving people's causal judgments. Given the predictability of the normally acting agent's behaviour, the abnormal agent is in a better position to foresee the consequences of their action. We put this hypothesis to test in four experiments. In Experiment 1, we show that people judge the atypical agent as more causal than the normally acting agent, but also perceive an epistemic advantage of the abnormal agent. In Experiment 2, we find that people do not judge a causal difference if there is no epistemic asymmetry between the agents. In Experiment 3, we replicate these findings for a scenario in which the abnormal agent's epistemic advantage generalises to a novel context. In Experiment 4, we extend these findings to mental states more broadly construed. We develop a Bayesian Network model that predicts the degree of mental states based on action normality and epistemic states, and find that people infer mental states like desire and intentions to a greater extent from abnormal behaviour. We discuss these results in light of current theories and research on people’s preference for atypical causes.

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Amplification in the Evaluation of Emotional Expressions Over Time

10.31234/osf.io/rfgy3 ◽

2021 ◽

Author(s):

Amit Goldenberg ◽

Jonas Schöne ◽

Ziyang Huang ◽

Timothy Sweeny ◽

Desmond C. Ong ◽

...

Keyword(s):

Social Cognition ◽

Social Interaction ◽

Computational Model ◽

Social Interactions ◽

Emotional Responses ◽

Current Paper ◽

Emotional Expressions ◽

Emotional Intensity ◽

Sequential Information ◽

Over Time

Social interactions are dynamic, and unfold over time. To make sense of social interactions, people must aggregate sequential information into summary, global evaluations. But how do people do this? To address this question, we conducted 9 studies (N= 1,583), using a diverse set of stimuli. Our focus was a central aspect of social interaction, namely the evaluation of others’ emotional responses. Results suggest that when aggregating sequences of images and videos expressing varying degrees of emotions, perceivers overestimate the sequence’s average emotional intensity. This tendency for overestimation, which we term the sequential amplification effect, is driven by stronger memory of more emotional expressions. A computational model further supports the memory account, and shows that amplification cannot be driven merely by perception. The current paper is the first to demonstrate amplification in social cognition of sequential information, which is especially important given the prevalence of such information in many social interactions.

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A Categorical Characterization of a ①-Iteratively De ned State of Common Knowledge

Contributions to Game Theory and Management ◽

10.21638/11701/spbu31.2021.24 ◽

2021 ◽

Vol 14 ◽

pp. 329-341

Author(s):

Fernando Tohmé ◽

◽

Gianluca Caterina ◽

Rocco Gangle ◽

◽

...

Keyword(s):

Fixed Point ◽

Category Theory ◽

Common Knowledge ◽

Epistemic State ◽

Knowledge Based ◽

Epistemic States ◽

Novel Approach

We present here a novel approach to the analysis of common knowledge based on category theory. In particular, we model the global epistemic state for a given set of agents through a hierarchy of beliefs represented by a presheaf construction. Then, by employing the properties of a categorical monad, we prove the existence of a state, obtained in an iterative fashion, in which all agents acquire common knowledge of some underlying statement. In order to guarantee the existence of a fixed point under certain suitable conditions, we make use of the properties entailed by Sergeyev's numeral system called grossone, which allows a finer control on the relevant structure of the infinitely nested epistemic states.

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Ignorance implicatures of modified numerals

Linguistics and Philosophy ◽

10.1007/s10988-021-09336-9 ◽

2021 ◽

Author(s):

Alexandre Cremers ◽

Liz Coppock ◽

Jakub Dotlačil ◽

Floris Roelofsen

Keyword(s):

Language Acquisition ◽

Higher Order ◽

Epistemic State ◽

Experimental Setting ◽

Natural Explanation ◽

Task Effect ◽

Series Of Experiments ◽

Question Under Discussion ◽

Modified Numerals ◽

Inference Task

AbstractModified numerals, such as at least three and more than five, are known to sometimes give rise to ignorance inferences. However, there is disagreement in the literature regarding the nature of these inferences, their context dependence, and differences between at least and more than. We present a series of experiments which sheds new light on these issues. Our results show that (a) the ignorance inferences of at least are more robust than those of more than, (b) the presence and strength of the ignorance inferences triggered by both at least and more than depends on the question under discussion (QUD), and (c) whether ignorance inferences are detected in a given experimental setting depends partly on the task that participants are asked to perform (e.g., an acceptability task versus an inference task). We offer an Optimality Theoretic account of these findings. In particular, the task effect is captured by assuming that in performing an acceptability task, participants take the speaker’s perspective in order to determine whether an expression is optimal given a certain epistemic state, while in performing an inference task they take the addressee’s perspective in order to determine what the most likely epistemic state of the speaker is given a certain expression. To execute the latter task in a fully rational manner, participants have to perform higher-order reasoning about alternative expressions the speaker could have used. Under the assumption that participants do not always perform such higher-order reasoning but also often resort to so-called unidirectional optimization, the task effect finds a natural explanation. This also allows us to relate our finding to asymmetries between comprehension and production that have been found in language acquisition.

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Doubt as a mechanism of the change of epistemic states (on the materials of the philosophy of pragmatism and neuropsychology)

Izvestiya of Saratov University New Series Series Philosophy Psychology Pedagogy ◽

10.18500/1819-7671-2021-21-4-367-371 ◽

2021 ◽

Vol 21 (4) ◽

pp. 367-371

Author(s):

Anastasia V. Golubinskaya ◽

Keyword(s):

Cognitive Process ◽

Cognitive Activity ◽

Interdisciplinary Approach ◽

The State ◽

Epistemic State ◽

Alternative View ◽

Cognitive Mechanisms ◽

Epistemic States ◽

Material Substance ◽

Neuropsychological Factors

Science has not yet found a solution to the question of how cognitive mechanisms, which are crucial for the subjective processes of evaluating the reliability of information and doubt, are arranged. This ability is usually associated with both the pragmatic consequences of accepting a belief and the material substance of consciousness. In this article, the author proposes to compare one of the largest conceptions of doubt in philosophy, the pragmatic conception, with the theory of false tags, which was presented in the last decade by the neuropsychologist E. Asp in order to explain the phenomena of doubt. The article presents the theoretical aspects of both conceptions, which allows to derive the properties of doubt as an epistemic state, that is, the state of the subject’s cognitive reality, formed under the influence of external (situational, pragmatic) and internal (neuropsychological) factors. The results of the study presented in the article allow us to conclude the possibility of an interdisciplinary approach in further studies of human cognitive activity as a mechanism of various epistemic states. It is concluded that doubt itself is not one of these states, but is a secondary psychological act that ensures the transition from one epistemic state to another. This offers an alternative view to the approach established in philosophy, in which doubt precedes the fact of accepting knowledge and is an essential stage of the cognitive process.

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