9,224 research outputs found
Temporal Data Modeling and Reasoning for Information Systems
Temporal knowledge representation and reasoning is a major research field in Artificial
Intelligence, in Database Systems, and in Web and Semantic Web research. The ability to
model and process time and calendar data is essential for many applications like appointment
scheduling, planning, Web services, temporal and active database systems, adaptive
Web applications, and mobile computing applications. This article aims at three complementary
goals. First, to provide with a general background in temporal data modeling
and reasoning approaches. Second, to serve as an orientation guide for further specific
reading. Third, to point to new application fields and research perspectives on temporal
knowledge representation and reasoning in the Web and Semantic Web
Quantum metalanguage and the new cognitive synthesis
Problems with mechanisms of thinking and cognition in many ways remain unresolved. Why are a priori inferences possible? Why can a human understand but a computer cannot? It has been shown that when creating new concepts, generalization is contradictory in the sense that to be created concepts must exist a priori, and therefore, they are not new. The process of knowledge acquisition is also contradictory, as it inevitably involves recognition, which can be realized only when there is an a priori standard. Known approaches of the framework of artificial intelligence (in particular, Bayesian) do not determine the origins of knowledge, as these approaches are effective only when “good” hypotheses are made. The formation of “good” hypotheses must occur a priori. To address these issues and paradoxes, a fundamentally new approach to problems of cognition that is based on completely innate behavioral programs is proposed. The process of cognition within the framework of the concept of a quantum metalanguage involves the selection of adequate a priori existing (innate) programs (logical variables and rules for working with them) that are most adequate to a given situation. The quantum properties of this metalanguage are necessary to implement such programs. © 2019, Anka Publishers. All rights reserved
Quantum metalanguage and the new cognitive synthesis
Problems with mechanisms of thinking and cognition in many ways remain unresolved. Why are a priori inferences possible? Why can a human understand but a computer cannot? It has been shown that when creating new concepts, generalization is contradictory in the sense that to be created concepts must exist a priori, and therefore, they are not new. The process of knowledge acquisition is also contradictory, as it inevitably involves recognition, which can be realized only when there is an a priori standard. Known approaches of the framework of artificial intelligence (in particular, Bayesian) do not determine the origins of knowledge, as these approaches are effective only when “good” hypotheses are made. The formation of “good” hypotheses must occur a priori. To address these issues and paradoxes, a fundamentally new approach to problems of cognition that is based on completely innate behavioral programs is proposed. The process of cognition within the framework of the concept of a quantum metalanguage involves the selection of adequate a priori existing (innate) programs (logical variables and rules for working with them) that are most adequate to a given situation. The quantum properties of this metalanguage are necessary to implement such programs
Luovat järjestelmät, toimijat sekä yhteisöt : Teoreettisia analyysimenetelmiä ja empiirisiä yhteistyötutkimuksia
Creativity is a multi-faceted phenomenon that can be observed in diverse individuals and contexts, both natural and artificial. This thesis studies computational creativity, i.e. creativity in machines, which can be broadly categorised as a subfield of artificial intelligence. In particular, the thesis deals with three important perspectives on computational creativity: (1) identifying properties of creative individuals, (2) studying processes that lead to creative outcomes, and (3) observing and analysing social aspects of creativity, e.g. collaboration which may allow the individuals to create something together which they could not do alone.
One of the key interests in computational creativity is how computational entities may exhibit creativity in their own right, implying that the creative entities and their compositions, roles, processes and interactions are potentially different from those encountered in nature. This calls for theoretical analysis methods specifically tailored for artificial creative entities, and carefully controlled empirical experiments and simulations with them. We study both of these aspects. The analysis methods allow us to scrutinise exactly how creativity occurs in artificial entities by providing appropriate conceptual elements and vocabulary, while experiments enable us to test and confirm the effectiveness of different design decisions considering individual artificial creative entities and their interaction with each other.
We propose three novel, domain-general analysis tools for artificial creative entities, i.e. creative systems and creative agents, and collections of them, called creative societies. First, we distinguish several conceptual components relevant for metacreative systems, i.e. systems that can reflect and control their creative behaviour, and discuss how these components are interlinked and affect the system's creativity. Second, we merge elements from sequential decision making in intelligent agents, i.e. Markov Decision Processes, into formal creativity as search model called the Creative Systems Framework, providing a detailed account of various elements which compose the decision-making process of a creative agent. Third, we map elements from an eminent social creativity theory, the Systems View of Creativity, a.k.a. Domain-Individual-Field-Interaction model, into the elements of the Creative Systems Framework and show how creative societies may be analysed formally with it.
Each of the proposed analysis tools provides new ways to analyse creativity in artificial entities. The analysis of metacreative systems assumes an architectural point of view to creativity, which has not been previously addressed in detail. Deconstructing the decision-making process of a creative agent gives us additional means to discuss and understand why or how a creative agent selects certain actions. Lastly, the contributions to the creative societies are the first formal framework for their analysis.
We also investigate in two consecutive case studies collaborator selection in creative societies. In the first study, we focus on what kind of cues, e.g. selfish or altruistic, assist in choosing beneficial collaboration partners when all the agents can observe from their peers are the individually created end products. The second study allows the agents to adjust their aesthetic preferences during the simulations and inspects what emerges from society as a whole. We conclude that selfish cues seem to be more effective in choosing the collaboration partners in our settings and that the society exhibits distinct emergence depending on how much the agents are willing to change their aesthetic preferences.Luovuus on monitahoinen ilmiö, jonka osatekijöitä voidaan tunnistaa monissa eri asiayhteyksissä. Tässä väitöskirjassa käsitellään laskennallista luovuutta, eli luovuutta koneissa, mikä voidaan karkeasti luokitella tekoälyn yhdeksi osa-alueeksi.
Yksi laskennallisen luovuuden tärkeimmistä kiinnostuksen kohteista tutkii miten koneet voivat olla luovia omasta ansiostaan. Tämä tarkoittaa että luovat järjestelmät ja toimijat, menetelmät, yhteisöt sekä niiden vuorovaikutus voivat erota ihmisten vastaavista. On siis tärkeää kyetä keskustelemaan luovien järjestelmien, toimijoiden ja yhteisöjen ominaisuuksista riippumatta niiden toteutuksien yksityiskohdista sekä suunnittelemaan simulaatioita ja kokeita joissa voidaan todentaa suunnitteluratkaisujen vaikutukset järjestelmän luovuudelle.
Väitöskirja esittelee kolme uutta luovuuden analyysimenetelmää, jotka on kehitetty analysoimaan (1) luovia järjestelmiä, (2) luovia toimijoita sekä (3) luovia agenttiyhteisöjä. Lisäksi kahdessa osajulkaisussa tutkitaan yhteistyöprosesseja simuloiduissa yhteisöissä, joissa itsenäiset luovat toimijat tuottavat abstraktia taidetta evolutiivisia menetelmiä käyttäen.
Ehdotetut analyysimenetelmät mahdollistavat luovuuden monialaisen tarkastelun sekä tarjoavat yhden mahdollisen suunnan kohti laskennallisen luovuuden yhtenäistä analyysimenetelmää. Havainnot empiirisistä simulaatioista antavat uutta tietoa laskennallisista yhteistyöprosesseista ja ovat askel kohti monimutkaisempia kokeita luovan yhteistyön saralla
Trends in Advertising: How the Rise in Artificial Intelligence May Influence the Field of Content Strategy
Whereas prior research on artificial intelligence has dealt with automation in fields like medicine, engineering, and computer science, this research study seeks to answer the question, “To what extent can AI be creative in the context of content strategy?” To answer this, this study employs content analysis using 16 online news and blog articles from primarily marketing organizations to identify and explain key variables surrounding the relationship between the computer and the creative professional. This study has found that the core belief that AI will play the future role of creative assistant in the context of content strategy is shared among many online marketing publications. As AI becomes increasingly capable of taking on lower level creative tasks such as content organization, ideation, basic copywriting, and photo editing, many believe this will open up more time for content strategy professionals to accomplish more creatively demanding, big picture tasks
Artificial general intelligence: Proceedings of the Second Conference on Artificial General Intelligence, AGI 2009, Arlington, Virginia, USA, March 6-9, 2009
Artificial General Intelligence (AGI) research focuses on the original and ultimate goal of AI – to create broad human-like and transhuman intelligence, by exploring all available paths, including theoretical and experimental computer science, cognitive science, neuroscience, and innovative interdisciplinary methodologies. Due to the difficulty of this task, for the last few decades the majority of AI researchers have focused on what has been called narrow AI – the production of AI systems displaying intelligence regarding specific, highly constrained tasks. In
recent years, however, more and more researchers have recognized the necessity – and feasibility – of returning to the original goals of the field. Increasingly, there is a call for a transition back to confronting the more difficult issues of human level intelligence and more broadly artificial general intelligence
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Brain Waves, A Cultural History: Oscillations of Neuroscience, Technology, Telepathy, and Transcendence
This project proceeds from a narrow question: What, if anything, is a brain wave? Beguiling in its simplicity, this question prompts a cultural-historical investigation that spans over 150 years of science, technology, and society. Proposed in 1869, the original theory of brain waves cites etheric undulations to explain reports of apparent thought transference. Though most modern thinkers no longer believe in outright telepathy, I argue that dreams of thought transmission and other mental miracles subtly persist—not in obscure and occult circles, but at the forefront of technoscience.
A hybrid of science and fiction, brain waves represent an ideal subject through which to explore the ways in which technical language shrouds spiritual dreams. Today, the phrase “brain waves” often function as shorthand for electrical changes in the brain, particularly in the context of technologies that purport to “read” some aspect of mental function, or to transmit neural data to a digital device. While such technologies appear uniquely modern, the history of brain waves reveals that they are merely the millennial incarnation of a much older hope—a hope for transmission and transcendence via the brain’s emanations
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