Partial Knowledge | ScienceGate

AbstractMany animal populations include a diversity of personalities, and these personalities are often linked to foraging strategy. However, it is not always clear why populations should evolve to have this diversity. Indeed, optimal foraging theory typically seeks out a single optimal strategy for individuals in a population. So why do we, in fact, see a variety of strategies existing in a single population? Here, we aim to provide insight into this conundrum by modelling the particular case of foraging seabirds, that forage on patchy prey. These seabirds have only partial knowledge of their environment: they do not know exactly where the next patch will emerge, but they may have some understanding of which locations are more likely to lead to patch emergence than others. Many existing optimal foraging studies assume either complete knowledge (e.g. Marginal Value Theorem) or no knowledge (e.g. Lévy Flight Hypothesis), but here we construct a new modelling approach which incorporates partial knowledge. In our model, different foraging strategies are favoured by different birds along the bold-shy personality continuum, so we can assess the optimality of a personality type. We show that it is optimal to be shy (resp. bold) when living in a population of bold (resp. shy) birds. This observation gives a plausible mechanism behind the emergence of diverse personalities. We also show that environmental degradation is likely to favour shyer birds and cause a decrease in diversity of personality over time.

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Using partial knowledge to inform the creation of learning progressions

Australian Journal of Education ◽

10.1177/00049441211037409 ◽

2021 ◽

pp. 000494412110374

Author(s):

Joan Burfitt

Keyword(s):

Secondary Students ◽

Conceptual Understanding ◽

Rasch Analysis ◽

Mathematics Assessment ◽

Learning Activities ◽

Learning Progressions ◽

Partial Knowledge ◽

Partial Credit ◽

Logical Order ◽

To Receive

The aim of this study was to show that some of the errors made by students when responding to mathematics assessment items can indicate progress in the development of conceptual understanding. By granting partial credit for specific incorrect responses by early secondary students, estimates of the difficulty of demonstrating full and partial knowledge of skills associated with the development of proportional reasoning were determined using Rasch analysis. The errors were confirmed as indicators of progress, and hence partial knowledge, when the thresholds of achievement followed a logical order: The greater the proficiency of the students, the more likely they were to receive a higher score. Consideration of this partial knowledge can enhance the descriptions of the likely behaviours of students at the various levels of learning progressions and this can be informative for teachers in their planning of learning activities.

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Misinformation, partial knowledge and guessing in true/false tests

Medical Education ◽

10.1046/j.1365-2923.2002.01299.x ◽

2002 ◽

Vol 36 (9) ◽

pp. 805-811 ◽

Cited By ~ 25

Author(s):

Richard F Burton

Keyword(s):

Partial Knowledge ◽

True False

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PARTIAL KNOWLEDGE AND BELIEF FUNCTIONS

A First Course in Fuzzy Logic ◽

10.1201/9781420057102-12 ◽

2005 ◽

pp. 281-328

Keyword(s):

Belief Functions ◽

Partial Knowledge

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A partial knowledge of friends of friends speeds social search

PLoS ONE ◽

10.1371/journal.pone.0255982 ◽

2021 ◽

Vol 16 (8) ◽

pp. e0255982

Author(s):

Amr Elsisy ◽

Boleslaw K. Szymanski ◽

Jasmine A. Plum ◽

Miao Qi ◽

Alex Pentland

Keyword(s):

Social Network ◽

Human Mobility ◽

Sufficient Conditions ◽

Partial Knowledge ◽

Social Search ◽

Strongly Nonlinear ◽

Original Distribution ◽

Personal Connections ◽

Location Based Social Network ◽

Necessary And Sufficient

Milgram empirically showed that people knowing only connections to their friends could locate any person in the U.S. in a few steps. Later research showed that social network topology enables a node aware of its full routing to find an arbitrary target in even fewer steps. Yet, the success of people in forwarding efficiently knowing only personal connections is still not fully explained. To study this problem, we emulate it on a real location-based social network, Gowalla. It provides explicit information about friends and temporal locations of each user useful for studies of human mobility. Here, we use it to conduct a massive computational experiment to establish new necessary and sufficient conditions for achieving social search efficiency. The results demonstrate that only the distribution of friendship edges and the partial knowledge of friends of friends are essential and sufficient for the efficiency of social search. Surprisingly, the efficiency of the search using the original distribution of friendship edges is not dependent on how the nodes are distributed into space. Moreover, the effect of using a limited knowledge that each node possesses about friends of its friends is strongly nonlinear. We show that gains of such use grow statistically significantly only when this knowledge is limited to a small fraction of friends of friends.

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A Scalable P2P RIA Crawling System with Partial Knowledge

Networked Systems - Lecture Notes in Computer Science ◽

10.1007/978-3-319-09581-3_13 ◽

2014 ◽

pp. 185-199 ◽

Cited By ~ 1

Author(s):

Khaled Ben Hafaiedh ◽

Gregor von Bochmann ◽

Guy-Vincent Jourdan ◽

Iosif Viorel Onut

Keyword(s):

Partial Knowledge

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A Novel User Collusion-Resistant Decentralized Multi-Authority Attribute-Based Encryption Scheme Using the Deposit on a Blockchain

Wireless Communications and Mobile Computing ◽

10.1155/2021/9506796 ◽

2021 ◽

Vol 2021 ◽

pp. 1-15

Author(s):

Siwan Noh ◽

Donghyun Kim ◽

Zhipeng Cai ◽

Kyung-Hyune Rhee

Keyword(s):

The Other ◽

Central Authority ◽

Partial Knowledge ◽

Trading Systems ◽

Main Motivation ◽

Attribute Based Encryption ◽

Secret Keys ◽

User Data ◽

Full Knowledge ◽

User Centric

Recently, the concept of a decentralized data marketplace is getting much attention to exchange user data. Multi-authority attribute-based encryption (ABE), which can provide flexibility and user-centric access control, is previously widely used in decentralized data sharing applications and also becoming a foundation to build decentralized data trading applications. It is known that users in a multi-authority ABE system can collude by sharing their secret information for malicious purposes. To address this issue, the collusion-resistant multi-authority ABE model was introduced in which a unique global identifier (GID) is issued by the central authority (CA) to each user. Unfortunately, such approach cannot be used directly to build a decentralized data marketplace as (a) such intervention of the CA is directly against the main motivation of the decentralized trading platform and, mostly importantly, (b) the CA can exploit its full knowledge on users’ GID to launch various attacks against users. Motivated by these observations, this paper introduces a novel user collusion-resistant decentralized multi-authority ABE scheme for privacy preserving data trading systems. In the existing multi-authority ABE systems, users utilize his/her GID that is solely assigned by the CA to generate his/her secret keys throughout the collaboration with authorities and a user can compute multi-authority keys by combining the secret keys (stem from the same GID) in various ways. In the proposed system, the CA only has a partial knowledge of users’ GIDs, and thus, users’ privacy can be protected. On the other hand, we set the user’s own partial GID as a secret which can be used to withdraw his/her deposit to discourage any possible collusion among users.

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