Logics of Informational Interactions

Baltag, Alexandru; Smets, Sonja

doi:10.1007/s10992-015-9345-y

Cited by 6 publications

(7 citation statements)

References 33 publications

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“…Yet another direction for future work is to look at possibilities for reasoning about the balance measures in the object language. This would be challenging, among other things because the measures are not invariant under bisimulation (the latter point could be alleviated by requiring all agents to be named by some nominal 9 ). On a final note, in light of logical analyses of social concepts it could be interesting to give certain attributes to agents in the network.…”

Section: Discussion Conclusion and Future Workmentioning

confidence: 99%

“…On a final note, in light of logical analyses of social concepts it could be interesting to give certain attributes to agents in the network. One alternative is knowledge, as in social epistemic frameworks such as [9,10,33,38]: could a polarized setting change depending on what agents know about their social situations? Another is communication: by implementing an information flow in the network we could analyze which agents are likely to become friends based on information and information access, e.g., by adopting a dynamic epistemic logic approach including public and private announcements [19].…”

Section: Discussion Conclusion and Future Workmentioning

confidence: 99%

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Modal Logics and Group Polarization

Pedersen

Smets

Ågotnes

2021

Journal of Logic and Computation

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This paper proposes different ways of modally defining properties related to the concept of balance in signed social networks where relations can be either positive or negative. The motivation is to be able to formally reason about the social phenomenon of group polarization based on balance theory. The starting point is a recently developed basic modal logic that axiomatizes the class of social networks that are balanced up to a certain degree. This property is not modally definable but can be captured using a deduction rule. In this work, we examine different possibilities for extending this basic language to define frame properties such as balance and related properties such as non-overlapping positive and negative relations and collective connectedness as axioms. Furthermore, we define the property of full balance rather than balanced-up-to-a-degree. We look into the complexity of the model checking problem and show a non-compactness result of the extended language. Along the way, we provide axioms for weak balance. We also look at a full hybrid extension and reason about network changes with dynamic modalities. Then, to explore the measures of how far a network is from polarization, we consider variations of measures in relation to balance.

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Section: Discussion Conclusion and Future Workmentioning

confidence: 99%

Section: Discussion Conclusion and Future Workmentioning

confidence: 99%

Modal Logics and Group Polarization

Pedersen

Smets

Ågotnes

2021

Journal of Logic and Computation

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“…One can use multiple techniques such as computer simulations, models in decision theory, etc., in order to assess the epistemic efficiency of a group. For instance, prominent approaches for investigating epistemic efficiencies from the perspective of philosophy of science are based on computer simulations (Kelly & Mayo-Wilson, 2010 ; Zollman, 2007 , 2010 ) and logical models (Baltag et al, 2013 ).…”

Section: Motivation: Efficiency In Producing Scientific Knowledgementioning

confidence: 99%

Machine learning in scientific grant review: algorithmically predicting project efficiency in high energy physics

Sikimić

Radovanović

2022

Euro Jnl Phil Sci

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As more objections have been raised against grant peer-review for being costly and time-consuming, the legitimate question arises whether machine learning algorithms could help assess the epistemic efficiency of the proposed projects. As a case study, we investigated whether project efficiency in high energy physics (HEP) can be algorithmically predicted based on the data from the proposal. To analyze the potential of algorithmic prediction in HEP, we conducted a study on data about the structure (project duration, team number, and team size) and outcomes (citations per paper) of HEP experiments with the goal of predicting their efficiency. In the first step, we assessed the project efficiency using Data Envelopment Analysis (DEA) of 67 experiments conducted in the HEP laboratory Fermilab. In the second step, we employed predictive algorithms to detect which team structures maximize the epistemic performance of an expert group. For this purpose, we used the efficiency scores obtained by DEA and applied predictive algorithms – lasso and ridge linear regression, neural network, and gradient boosted trees – on them. The results of the predictive analyses show moderately high accuracy (mean absolute error equal to 0.123), indicating that they can be beneficial as one of the steps in grant review. Still, their applicability in practice should be approached with caution. Some of the limitations of the algorithmic approach are the unreliability of citation patterns, unobservable variables that influence scientific success, and the potential predictability of the model.

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“…One of the latest development in this way is quantum modal logics. The research have been done by A. Baltag and S. Smets [4,5], F. Boge [8], V. Vilasini [22] and N. Nurgalieva [17]. Our study covers field of logic of correlated knowledge which is part of quantum modal logics.…”

Section: Introductionmentioning

confidence: 99%

Automated Proof Search System for Logic of Correlated Knowledge

Giedra¹,

Alonderis²

2020

AJMCM

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Logic of correlated knowledge is one of the latest development in logical systems, allowing to handle information about quantum systems. Quantum system may consist of one or more elementary particles. Associating agent to each particle, we get multi-agent system, where agents can perform observations and get results. Allowing communication between agents, correlations such as quantum entanglement can be extracted. This can not be done by traditional epistemic logic or logic of distributed knowledge. Our main scientific result is proof search system GS-LCK-PROC for logic of correlated knowledge, which lets to reason about knowledge automatically. The core of the system is the sequent calculus GS-LCK with the properties of soundness, completeness, admissibility of cut and structural rules, and invertibility of all rules. The ideas of semantic internalization are used to get such properties for the calculus. The calculus provides convenient means for backward proof search and decision procedure for logic of correlated knowledge. The procedure generates a finite model for each sequent. As a result we get termination of the proof search and decidability of logic of correlated knowledge.

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Logics of Informational Interactions

Cited by 6 publications

References 33 publications

Modal Logics and Group Polarization

Modal Logics and Group Polarization

Machine learning in scientific grant review: algorithmically predicting project efficiency in high energy physics

Automated Proof Search System for Logic of Correlated Knowledge

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