An egocentric semantic reference system for affordances

Ortmann, Jens; Felice, Giorgio De; Wang, Dong; Daniel, Desiree

doi:10.3233/sw-130119

Cited by 4 publications

(3 citation statements)

References 38 publications

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“…Şahin et al (2007) argue for the relevance of the observer perspective to affordance-based robot control. Although not being referred to in their argument, examples to illustrate the observer perspective may include Ortmann & Kuhn's (2010 extension of their ontology of observation to Turvey's (1992) dispositional account of affordances and its application to what Ortmann et al (2014) call an "egocentric semantic reference system for affordances"; as well as Beßler et al's (2020) definition of affordances as "descriptions of dispositions" (rather than as dispositions themselves) in ameliorating autonomous robot control (Beßler et al, 2021).…”

Section: Observer Perspectivementioning

confidence: 99%

Affordances and their ontological core

Toyoshima

Barton

Éthier

2022

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The notion of affordance remains elusive, notwithstanding its importance for the representation of agency, cognition, and behaviors. This paper lays down a foundation for an ontology of affordances by elaborating the idea of “core affordance” which would serve as a common ground for explaining existing diverse conceptions of affordances and their interrelationships. For this purpose, it analyzes M. T. Turvey’s dispositional theory of affordances in light of a formal ontology of dispositions. Consequently, two kinds of so-called “core affordances” are proposed: specific and general ones. Inspired directly by Turvey’s original account, a specific core affordance is intimately connected to a specific agent, as it is reciprocal with a counterpart effectivity (which is a disposition) of this agent within the agent-environment system. On the opposite, a general core affordance does not depend on individual agents; rather, its realization involves an action by an instance of a determinate class of agents. The utility of such core affordances is illustrated by examining how they can be leveraged to formalize other major accounts of affordances. Additionally, it is briefly outlined how core affordances can be employed to analyze three notions that are closely allied with affordances: the environment, image schemas, and intentions.

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Section: Observer Perspectivementioning

confidence: 99%

Affordances and their ontological core

Toyoshima

Barton

Éthier

2022

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“…In addition, to avoid misunderstandings or a lack of shared understanding, we need approaches to inter-compare and translate between diverse BoK as a prerequisite for fruitful negotiations between such different actors. In other words (and in addition to reference systems that express and translate spatial-temporal information), we need a new generation of semantic reference systems (Kuhn 2003;Ortmann et al 2014) that allow us to formalize our BoK and their interrelationships to the full extent. A semantic reference system constitutes two parts (Janowicz and Scheider 2010).…”

Section: Digital Earth and The Co-creation And Communication Approachmentioning

confidence: 99%

Big Earth Data science: an information framework for a sustainable planet

Guo

Nativi

Liang

et al. 2020

International Journal of Digital Earth

101

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The digital transformation of our society coupled with the increasing exploitation of natural resources makes sustainability challenges more complex and dynamic than ever before. These changes will unlikely stop or even decelerate in the near future. There is an urgent need for a new scientific approach and an advanced form of evidence-based decisionmaking towards the benefit of society, the economy, and the environment. To understand the impacts and interrelationships between humans as a society and natural Earth system processes, we propose a new engineering discipline, Big Earth Data science. This science is called to provide the methodologies and tools to generate knowledge from diverse, numerous, and complex data sources necessary to ensure a sustainable human society essential for the preservation of planet Earth. Big Earth Data science aims at utilizing data from Earth observation and social sensing and develop theories for understanding the mechanisms of how such a social-physical system operates and evolves. The manuscript introduces the universe of discourse characterizing this new science, its foundational paradigms and methodologies, and a possible technological framework to be implemented by applying an ecosystem approach. CASEarth and GEOSS are presented as examples of international implementation attempts. Conclusions discuss important challenges and collaboration opportunities. ARTICLE HISTORY

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“…There exist few examples of ontologies conceptualising the idea of affordances. In literature, the notion of affordance has been seen either as the relation between the environment and an agent [198], or as qualities of objects in the environment taken with reference to an observer [159,158,190]. Our approach is closer to the characterisation proposed by Stoffregen [198], albeit we abstract the notion environment to a more general concept of situation as conceived by Gangemi and Mika [84].…”

Section: Affordance Ontologymentioning

confidence: 99%

Engineering Background Knowledge for Social Robots

Asprino

2020

Studies on the Semantic Web

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Riconosco che questo questo lavoroè frutto di un percorso iniziato molti anni fa sui banchi di scuola e se oggi presento una tesi di dottorato lo devo a molte persone. Vorrei iniziare dai miei genitori perchè i loro sforzi mi hanno permesso di studiare in tutta tranquillità e perchè hanno sempre creduto in me e mi hanno incoraggiato in quello che facevo. Vorrei ringraziare le mie sorelle Rosa e Paola insieme con i loro mariti che mi hanno pazientemente sopportato durante gli anni di università. Sfrutto questa sezione per esprimere la mia riconoscenza per Fulvio, Iride, Sara ed Erminia che mi hanno accolto, ospitato, sfamato e aiutato come figlio/fratello. Vorrei inoltre dedicare questa tesi ai miei nipoti Maria Letizia, Anna Luce, Lorenzo, Vittoria e Lorena. Spero che possiate trovare anche voi un lavoro che vi appassioni e che vi renda soddisfatti giorno per giorno. Vorrei esprimere la mia più profonda gratitudine per la dr.ssa Valentina Presutti che nel 2015, credendo in me e nelle mie capacità, mi ha accettato nel suo gruppo di ricerca e in seguito mi ha guidato pazientemente per tutta la durata del dottorato. Un ringraziamento speciale lo devo al mio supervisore, prof. Paolo Ciancarini, per essere stato sempre pronto ad aiutarmi nelle mie difficoltà, per i suoi consigli e suggerimenti nelle attività di ricerca. Inoltre, vorrei ringraziare in modo particolare il prof. Aldo Gangemi per essersi sempre speso per trasferirmi le sue conoscenze allargando i miei orizzonti di ricerca. Vorrei esprimere la mia riconoscenza verso i revisori di questa tesi, la prof.ssa Eva Blomqvist e il dr. Fabien Gandon, perchè grazie ai loro commenti appassionati ho potuto migliorare questa tesi. Vorrei ringraziare il prof. vii Frank Van Harmelen e il dr. Wouter Beek perchè mi hanno calorosamente accolto e ospitato nel loro gruppo durante il mio periodo all'estero. Se sono quiè anche merito di alcuni professori che durante gli anni di università mi hanno trasmesso entusiasmo verso le materie scientifiche. Tra questi, vorrei ringraziare in modo particolare il prof. Giuseppe De Giacomo perchè la sua passione per l'intelligenza artificiale mi ha spinto verso il mondo accademico. Infine, la mia riconoscenza va a tutti i miei insegnanti e professori che si sono spesi per la mia formazione. Qui vorrei ricordarne alcuni a cui sarò sempre riconoscente: Maria Elena Coppa, prof. Vaccarone, prof.ssa Civale, prof.ssa Libertino e prof. Calabrese. Durante questi anni ho collaborato con diverse persone e anche questo lavoroè frutto del contributo di molti. In modo particolare vorrei esprimere la mia riconoscenza per Alessandro Russo e Andrea Giovanni Nuzzolese con i quali ho condiviso e continuo a condividere molte fatiche e lunghi "pellegrinaggi". Un grazie speciale va alle persone che hanno collaborato al lavoro presentato in questa tesi Mehwish

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An egocentric semantic reference system for affordances

Cited by 4 publications

References 38 publications

Affordances and their ontological core

Affordances and their ontological core

Big Earth Data science: an information framework for a sustainable planet

Engineering Background Knowledge for Social Robots

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