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Academic literature on the topic 'Beliefs'

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Published: 4 June 2021
Last updated: 30 July 2024

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Journal articles on the topic "Beliefs"

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Schwitzgebel, Eric. "Knowing Your Own Beliefs." Canadian Journal of Philosophy Supplementary Volume 35 (2009): 41–62. http://dx.doi.org/10.1080/00455091.2009.10717643.

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How do you know your own beliefs? And how well do you know them? The two questions are related. I'll recommend a pluralist answer to the first question. The answer to the second question, I'll suggest, varies depending on features of the case.Self-scanning. Shaun Nichols and Stephen Stich (2003) say this: You have in your mind a functionally defined “belief box.” To believe some propositionP is just to have a representation with the content “P” in the belief box. You also have a monitoring mechanism that can scan the contents of the belief box. Normally, you come to know what you believe by deploying that scanner, creating a new belief in the belief box, a belief with the content “I believe thatP.” Self-scanning accounts admit of many possible variations and complications (e.g., Armstrong 1968, 1981, 1999; Lycan 1996; Goldman 2006), but the basic idea is that people have one or more interior monitors or scanners that detect the presence of beliefs and produce, as output, beliefs about those beliefs (or judgments about those beliefs, or representations of those beliefs).
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Battigalli, Pierpaolo, and Giacomo Bonanno. "The Logic of Belief Persistence." Economics and Philosophy 13, no. 1 (April 1997): 39–59. http://dx.doi.org/10.1017/s0266267100004296.

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The principle of belief persistence, or conservativity principle, states that ‘When changing beliefs in response to new evidence, you should continue to believe as many of the old beliefs as possible’ (Harman, 1986, p. 46). In particular, this means that if an individual gets new information, she has to accommodate it in her new belief set (the set of propositions she believes), and, if the new information is not inconsistent with the old belief set, then (1) the individual has to maintain all the beliefs she previously had and (2) the change should be minimal in the sense that every proposition in the new belief set must be deducible from the union of the old belief set and the new information (see, e.g., Gärdenfors, 1988; Stalnaker, 1984). We focus on this minimal notion of belief persistence and characterize it both semantically and syntactically.
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Chappell, T. D. J. "Does Protagoras refute himself?" Classical Quarterly 45, no. 2 (December 1995): 333–38. http://dx.doi.org/10.1017/s0009838800043433.

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Protagoras believes that all beliefs are true. Since Protagoras' belief that all beliefs are true is itself a belief, it follows (somewhat trivially, perhaps?) from Protagoras' belief that all beliefs are true that Protagoras' belief is true. But what about the belief that Protagoras' belief is false? Doesn't it follow, by parallel reasoning and not at all trivially, that if all beliefs are true and there is a belief that Protagoras' belief is false, then Protagoras' belief is false?
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Williams, Peter. "Beliefs supporting belief." Philosophers' Magazine, no. 7 (1999): 56–57. http://dx.doi.org/10.5840/tpm1999768.

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PLANTINGA, ALVIN. "Swinburne and Plantinga on internal rationality." Religious Studies 37, no. 3 (September 2001): 357–58. http://dx.doi.org/10.1017/s0034412501225712.

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I took it that the definitions Swinburne quotes imply that all of a person's basic beliefs are (privately) rational; Swinburne demurs. It still seems to me that these definitions have this consequence. Let me briefly explain why. According to Swinburne, a person's evidence consists of his basic beliefs, weighted by his confidence in them. So presumably we are to think of S's evidence as the set of the beliefs he takes in the basic way, together with a sort of index indicating, for each of those beliefs, his degree of confidence in that belief. Now it is clear, first, that different basic beliefs can be held with different degrees of confidence. I believe 2+1 = 3 more firmly than there are presently some large trees in my backyard, and I believe that second proposition more firmly than I played bridge last night. Nevertheless, I believe all three propositions; I don't just believe them probably. So, the set of my basic beliefs contains propositions, all of which I believe. Further, a belief of mine is ‘rendered (evidentially) probable by [my] evidence’, I take it, just if it is probable with respect to the set of my basic beliefs. But of course probability of 1 with respect to that set; the degree of confidence with which I hold those beliefs does not seem to be relevant. Hence my conclusion that on these definitions all of my basic beliefs are rational.Swinburne points out that some of my basic beliefs may be improbable with respect to the rest of my basic beliefs; these beliefs, then, might be thought irrational, at least if they are not held as firmly as those with respect to which they are improbable. But this seems to me an uninteresting sense of ‘irrational’. Many of my basic beliefs are improbable with respect to my other basic beliefs; they are none the worse for that. I now remember, as it seems to me, that in the second bridge hand last night I was dealt three aces, three jacks, and three deuces. This is unlikely on the rest of my basic beliefs. It is, nonetheless, not irrational in any useful sense; memory is an important and independent source of rational belief, a source such that its deliverances do not necessarily depend, for warrant or rationality, on their probability with respect to other basic beliefs. I believe the same goes for some of my Christian beliefs. They may be improbable with respect to other beliefs, basic or otherwise, that I hold; but that need be nothing whatever against them.
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Alston, William P. "Does God have Beliefs?" Religious Studies 22, no. 3-4 (September 1986): 287–306. http://dx.doi.org/10.1017/s0034412500018333.

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Beliefs are freely attributed to God nowadays in Anglo–American philosophical theology. This practice undoubtedly reflects the twentieth–century popularity of the view that knowledge consists of true justified belief (perhaps with some needed fourth component). (After all no one supposes that God has beliefs in addition to, or instead of knowledge.) The connection is frequently made explicit. If knowledge is true justified belief then whatever God knows He believes. It would seem that much recent talk of divine beliefs stems from Nelson Pike's widely discussed article, ‘Divine Omniscience and Voluntary Action’. In this essay Pike develops a version of the classic argument for the incompatibility of divine foreknowledge and free will in terms of divine forebelief. He introduces this shift by premising that ‘A knows X’ entails ‘A believes X’. As a result of all this, philosophers have increasingly been using the concept of belief in defining ‘omniscience’.
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Vidal, Javier. "El autoconocimiento de las creencias: una objeción al método de la transparencia." Humanities Journal of Valparaiso, no. 14 (December 29, 2019): 429. http://dx.doi.org/10.22370/rhv2019iss14pp429-448.

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According to the method of transparency, genuine self-knowledge is the outcome of an inference from world to mind. A. Byrne (2018) has developed a theory in which the method of transparency consists in following an epistemic rule in order to form self-verifying second-order beliefs. In this paper, I argue that Byrne’s theory does not establish sufficient conditions for having self-knowledge of first-order beliefs. Examining a case of self-deception, I strive to show that following such a rule might not result in self-knowledge when one is involved in rational deliberation. In the case under consideration, one precisely comes to believe that one believes that p without coming to believe that p. The justification for one’s not forming the belief that p with its distinctive causal pattern in mental life and behaviour, is that one already had the unconscious belief that not-p, a belief that is not sensitive to the principles governing theoretical and practical reasoning.
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Samraj, Tennyson. "Epistemic Awareness of Doxastic Distinctions: Delineating Types of Beliefs in Belief-Formation." ATHENS JOURNAL OF PHILOSOPHY 1, no. 1 (January 20, 2022): 37–50. http://dx.doi.org/10.30958/ajphil.1-1-3.

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Doxastic distinctions help us define the basis and biases in belief–formation. Empirical and extra-empirical justification play an important role in determining doxastic distinctions. When we distinguish the different types of beliefs, we understand (1) that there are basically three kinds of beliefs, namely, verifiable, falsifiable, and unfalsifiable beliefs. Empirical justification provides the basis for establishing the veracity of verifiable and falsifiable beliefs. Extra-empirical justification provides the basis for establishing the veracity of unfalsifiable or irrefutable beliefs. (2) Verifiable or falsifiable beliefs that are reductive require the mandatory acceptance of their truth. However, unfalsifiable beliefs which are non-reductive require the volitional acceptance of their truth. Because there is both empirical and extra-empirical justification in belief-formation, we can accept beliefs with or without, against, or regardless of empirical evidence. Unfalsifiable beliefs do not mean that these beliefs are unjustifiable; it simply means that these beliefs are not empirically justifiable. Understanding the basis and biases of belief-formation is to be aware of how we come to know what we believe. As empirical basis allows us to hold beliefs based on either the principle of confirmation or falsification. Extra-empirical basis, namely phenomenological conjectures, allows us to hold beliefs founded on existential assertions. The intent of this paper is to present doxastic distinctions to help us understand the basis and biases associated with belief-formation. As long as epistemic claims are accepted, and their content is considered believable, the means used to arrive at those beliefs must also be respected. Every doxastic distinction not only provides the basis for belief-formation but also defines the role and limits of both empirical and extra-empirical justification in belief-formation. When we recognize the different types and different ways of justifying beliefs: we understand (1) why we can accept beliefs with or without evidence; against or regardless of empirical justification, and (2) know when to define beliefs as Plato argued as justified true belief and when to define beliefs as justified belief-decisions. Keywords: beliefs, justified true belief; justified belief-decisions, empirical and extra-empirical
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Prims, J. P. "Call it a conspiracy: How conspiracy belief predicts recognition of conspiracy theories." PLOS ONE 19, no. 4 (April 18, 2024): e0301601. http://dx.doi.org/10.1371/journal.pone.0301601.

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While conspiracy theories are treated as irrational fringe beliefs in popular culture, conspiracy belief is quite common. Given the disconnect between stereotypes about conspiracy belief and its prevalence, I tested whether people have difficulty recognizing the conspiracy theories that they believe as conspiracy theories. Across two studies I demonstrate that people have considerable difficulty identifying conspiracy theories they believe as conspiracy theories, particularly when they do not take much time to consider whether their beliefs might be conspiracy theories. This is consistent with the notion that people experience “conspiracy blindness.” People have trouble recognizing the conspiracy theories they believe as conspiracy theories because they do not take the time to consider whether their beliefs might be conspiracy theories. In Study 2, I demonstrate that people can overcome their conspiracy blindness and recognize the conspiracy theories they believe as conspiracy theories when they are given a definition for “conspiracy theory” and asked to consider their answer. This suggests that people are typically ignorant of their own conspiracy beliefs, but capable of recognizing them when given the tools and motivation to do so. However, recognizing their beliefs as conspiracy theories does not reduce their adherence to those beliefs.
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Donahue, Sean. "Knowledge exclusion and the rationality of belief." Analysis 79, no. 3 (December 6, 2018): 402–10. http://dx.doi.org/10.1093/analys/any078.

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Abstract Two epistemic principles are Knowledge Exclusion and Belief Exclusion. Knowledge Exclusion says that it is necessarily the case that if an agent knows that p, then she does not believe that ∼p, and Belief Exclusion says that it is necessarily the case that if an agent believes that q, then she does not believe that ∼q. Many epistemologists find it reasonable to reject the latter principle and accept the former. I argue that this is in fact not reasonable by proposing a case in which an agent can use that she has contradictory beliefs towards a proposition as decisive evidence for that proposition. A natural response is that this case conflicts with common assumptions about the relation between knowledge, contradictory beliefs and rationality. I reply by drawing ideas from Lasonen-Aarnio’s (2010) remarks on unreasonable knowledge to explain why these common assumptions do not threaten my argument.
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Dissertations / Theses on the topic "Beliefs"

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McClung, Samuel Alan. "Peer evaluator beliefs analyzed within a teacher belief framework." Diss., The University of Arizona, 1993. http://hdl.handle.net/10150/186587.

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The purpose of this study was to describe the views of peer evaluators within a career ladder system in one school district in the Southwestern United States. The methods and data analysis used 3 parts of a theoretical framework developed by Lortie (1975): goals sought in the workplace (perspectives on purpose), effective teaching (and the effects of endemic uncertainties of teaching to effectiveness), and preferences in job tasks (logic of sentiments). Eleven peer evaluators were interviewed. The data from the interviews were qualitatively analyzed and presented. Among the findings, peer evaluators' perspectives on purpose included goals to gain experience for leaving the classroom. Peer evaluators' endemic uncertainties included the assessment of teaching and the description of an effective teacher. Within peer evaluators' logic of sentiments, they preferred to observe students and work with teachers. Peer evaluators disliked determining the compensation of teachers. Within their logic of sentiments, peer evaluators viewed teachers as a well-qualified group willing to continue their own professional growth. Peer evaluators found their relationship with teachers constrained because of their roles of assisting teachers in their professional growth and summatively assessing teachers. Implications of this study include the need for further study to describe the views of teachers involved in differentiated staffing in career ladder programs. Additionally, further study is needed to determine the relationship of the views of teachers within a career ladder program to the success of the policies and activities of these programs.
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Santos, Clara Maria Melo dos. "Good reasoning : to whom? when? how?; an investigation of belief effects on syllogistic and argumentative reasoning." Thesis, University of Sussex, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.296530.

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Meier, Martin. "Universal beliefs structures." [S.l. : s.n.], 2002. http://deposit.ddb.de/cgi-bin/dokserv?idn=970851073.

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Jardin, Charles E. "Irrational Christian beliefs." Theological Research Exchange Network (TREN), 1985. http://www.tren.com.

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Queale, Peter R. "Oral health beliefs /." Title page, contents and abstract only, 1994. http://web4.library.adelaide.edu.au/theses/09AR.PS/09ar.psq3.pdf.

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Nye, Gary D. Adkison Judith Ann. "Principals' leadership beliefs." [Denton, Tex.] : University of North Texas, 2008. http://digital.library.unt.edu/permalink/meta-dc-9747.

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White, Cindel Jennifer Melina. "Belief in karma : the content and correlates of supernatural justice beliefs across cultures." Thesis, University of British Columbia, 2017. http://hdl.handle.net/2429/62559.

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Karmic beliefs, centered on the notion of ethical causation within and across lifetimes, appear in religious traditions and spiritual movements around the world, yet they remain an unexplored topic in psychology. I developed and validated a 16-item measure of belief in karma, and used this measure to assess the cultural distribution, cognitive content, and correlates of karmic beliefs among participants from culturally and religiously diverse backgrounds, including Canadian students (Sample 1: N = 3193, Sample 2: N = 3072) and broad national samples of adults from Canada (N = 1000) and India (N = 1006). Belief in karma showed predictable variation based on participant’s cultural (e.g., Indian) and religious (e.g., Hindu and Buddhist) background, but was also surprisingly common among people from cultural groups with no tradition of karmic beliefs (e.g., nonreligious or Christian Canadians). I demonstrate how karmic beliefs are related to, but distinct from, conceptually-similar beliefs, including belief in a just world and belief in a moralizing god. Finally, I provide preliminary evidence of intuitive conceptions of karma, and investigate how karma is related to self-reported prosocial behaviour and moral judgments. Karma is a form of supernatural justice belief, endorsed by many people from diverse cultural and religious backgrounds that lies at the intersection between beliefs about justice and morality, and beliefs about supernatural forces that shape the course of life’s events.
Arts, Faculty of
Psychology, Department of
Graduate
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Belcher, Devon. "On words: An essay on beliefs, belief attributions and the ontology of language." Diss., Connect to online resource, 2005. http://wwwlib.umi.com/dissertations/fullcit/3178358.

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Lawrence, Christopher. "Permission to believe: descriptive and prescriptive beliefs in the Clifford/James debate." Doctoral thesis, Faculty of Humanities, 2021. http://hdl.handle.net/11427/32789.

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William Clifford's ‘The Ethics of Belief' proposes an ‘evidence principle': …it is wrong always, everywhere, and for anyone, to believe anything upon insufficient evidence (1877, 1879:186). Its universal, absolutist language seems to hide something fundamentally correct. We first argue for excluding prescriptive beliefs, and then consider further apparent counter-examples, culminating in more restricted, qualified wording: If anything is morally wrong, then it is morally wrong within the category of descriptive belief to believe anything knowingly or irresponsibly on insufficient evidence in the absence of any conflicting and overriding moral imperative except when the unjustified believing is outside the believer's voluntary control. We test this against William James's counter-claim for qualified legitimate overbelief (‘The Will To Believe', 1896, 2000), and suggest additional benefits of adopting an evidence principle in relation to the structured combinations of descriptive and prescriptive components common to religious belief. In search of criteria for ‘sufficient' and ‘insufficient' evidence we then consider an ‘enriched' Bayesianism within normative decision theory, which helps explain good doxastic practice under risk. ‘Lottery paradox' cases however undermine the idea of an evidence threshold: we would say we justifiably believe one hypothesis while saying another, at the same credence level, is only very probably true. We consider approaches to ‘pragmatic encroachment', suggesting a parallel between ‘practical interest' and the ‘personal utility' denominating the stakes of the imaginary gambles which Bayesian credences can be illustrated as. But personal utility seems inappropriately agent-relative for a moral principle. We return to Clifford's conception of our shared responsibilities to our shared epistemic asset. This ‘practical interest we ought to have' offers an explanation for our duty, as members of an epistemic community, to get and evaluate evidence; and for the ‘utility' stakes of Bayesian imaginary gambles. Helped by Edward Craig's (1990, 1999) ‘state-of-nature' theory of knowledge it provides a minimum threshold to avoid insufficient evidence and suggests an aspirational criterion of sufficient evidence: Wherever possible, a level of evidence sufficient to support the level of justification required to be a good informant, whatever the particular circumstances of the inquirer.
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Lu, Xinyue. "Could Intuitions Be Beliefs?" Scholarship @ Claremont, 2015. http://scholarship.claremont.edu/scripps_theses/630.

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Books on the topic "Beliefs"

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Royle, Howard A. Beliefs, beliefs: Logic, faith. Canyonville, OR: Canyon Pub., 2002.

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Lowry, Alex. Beliefs. London: Groinkers' Press, 2013.

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Koedijk, Kees, and Alfred Slager. Investment Beliefs. London: Palgrave Macmillan UK, 2011. http://dx.doi.org/10.1057/9780230307575.

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Bar-Tal, Daniel. Group Beliefs. New York, NY: Springer New York, 1990. http://dx.doi.org/10.1007/978-1-4612-3298-8.

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Roberts, J. Deotis. Christian beliefs. 3rd ed. Silver Spring, MD: J. Deotis Roberts Press, 2000.

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Badawi, Jamal A. Muslim beliefs. Singapore: Muslim Converts' Association of Singapore, 2001.

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Hoggart, Simon. Bizarre beliefs. London: Richard Cohen Books, 1995.

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F, Oltmanns Thomas, and Maher Brendan A. 1924-, eds. Delusional beliefs. New York: Wiley, 1988.

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Jacob, Beaver, Kerridge Tobie, Pennington Sarah, and Engineering and Physical Sciences Research Council, eds. Material beliefs. London: Goldsmith's, University of London, 2009.

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Mike, Hutchinson, ed. Bizarre beliefs. London: R. Cohen Books, 1995.

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Book chapters on the topic "Beliefs"

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Alvarado, Sergio J. "Beliefs and Belief Relationships." In The Kluwer International Series in Engineering and Computer Science, 49–80. Boston, MA: Springer US, 1990. http://dx.doi.org/10.1007/978-1-4613-1561-2_3.

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Luger, Tana M. "Health Beliefs/Health Belief Model." In Encyclopedia of Behavioral Medicine, 999–1000. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-39903-0_1227.

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Orbell, Sheina, Havah Schneider, Sabrina Esbitt, Jeffrey S. Gonzalez, Jeffrey S. Gonzalez, Erica Shreck, Abigail Batchelder, et al. "Health Beliefs/Health Belief Model." In Encyclopedia of Behavioral Medicine, 907–8. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-1005-9_1227.

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Endsjø, Dag Øistein. "New Beliefs, Old Beliefs." In Greek Resurrection Beliefs and the Success of Christianity, 105–20. New York: Palgrave Macmillan US, 2009. http://dx.doi.org/10.1057/9780230622562_5.

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Schmitz, Angela. "Beliefs." In Freiburger Empirische Forschung in der Mathematikdidaktik, 107–45. Wiesbaden: Springer Fachmedien Wiesbaden, 2017. http://dx.doi.org/10.1007/978-3-658-18425-4_5.

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Griffiths, Carol, and Adem Soruç. "Beliefs." In Individual Differences in Language Learning, 149–64. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-52900-0_10.

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Carlitz, Adam, and Kimberly Rios. "Beliefs." In Encyclopedia of Personality and Individual Differences, 435–39. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-319-24612-3_1785.

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Cobern, William. "Beliefs." In Encyclopedia of Science Education, 1. Dordrecht: Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-007-6165-0_353-5.

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Barrett, Chad. "Beliefs." In Encyclopedia of Behavioral Medicine, 233–35. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-39903-0_1653.

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Wideman, Timothy H., Michael J. L. Sullivan, Shuji Inada, David McIntyre, Masayoshi Kumagai, Naoya Yahagi, J. Rick Turner, et al. "Beliefs." In Encyclopedia of Behavioral Medicine, 202–4. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-1005-9_1653.

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Conference papers on the topic "Beliefs"

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Delgrande, James P., Joshua Sack, Gerhard Lakemeyer, and Maurice Pagnucco. "Epistemic Logic of Likelihood and Belief." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/360.

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A major challenge in AI is dealing with uncertain information. While probabilistic approaches have been employed to address this issue, in many situations probabilities may not be available or may be unsuitable. As an alternative, qualitative approaches have been introduced to express that one event is no more probable than another. We provide an approach where an agent may reason deductively about notions of likelihood, and may hold beliefs where the subjective probability for a belief is less than 1. Thus, an agent can believe that p holds (with probability <1); and if the agent believes that q is more likely than p, then the agent will also believe q. Our language allows for arbitrary nesting of beliefs and qualitative likelihoods. We provide a sound and complete proof system for the logic with respect to an underlying probabilistic semantics, and show that the language is equivalent to a sublanguage with no nested modalities.
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Liu, Daxin, and Gerhard Lakemeyer. "Reasoning about Beliefs and Meta-Beliefs by Regression in an Expressive Probabilistic Action Logic." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/269.

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In a recent paper Belle and Lakemeyer proposed the logic DS, a probabilistic extension of a modal variant of the situation calculus with a model of belief based on weighted possible worlds. Among other things, they were able to precisely capture the beliefs of a probabilistic knowledge base in terms of the concept of only-believing. While intuitively appealing, the logic has a number of shortcomings. Perhaps the most severe is the limited expressiveness in that degrees of belief are restricted to constant rational numbers, which makes it impossible to express arbitrary belief distributions. In this paper we will address this and other shortcomings by extending the language and modifying the semantics of belief and only-believing. Among other things, we will show that belief retains many but not all of the properties of DS. Moreover, it turns out that only-believing arbitrary sentences, including those mentioning belief, is uniquely satisfiable in our logic. For an interesting class of knowledge bases we also show how reasoning about beliefs and meta-beliefs after performing noisy actions and sensing can be reduced to reasoning about the initial beliefs of an agent using a form of regression.
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A. McLaughlin, Laura, and James McLaughlin. "Framing the Innovation Mindset." In InSITE 2021: Informing Science + IT Education Conferences. Informing Science Institute, 2021. http://dx.doi.org/10.28945/4771.

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Aim/Purpose: To build the skills of innovation, we must first establish a framework for the belief system that surrounds effective innovation practice. In building any belief system, sometimes outdated beliefs need to be replaced with better, more carefully researched ideas. One such belief, discovered in our research and elsewhere, is that creativity is innate and that great ideas arise through chance or happenstance. Background: One belief regarding innovation and creativity, discovered in our research and elsewhere, is the belief that creativity is innate. History has repeatedly shown this to be untrue, yet people still believe it. We have found within our research another belief is that innovation happens through random, unstructured processes -- that great ideas arise through chance or happenstance. However, participants also believed that innovation is a skill. If someone believes innovation is a skill but also believes innovation is innate, random, and unstructured, this disconnect presents obstacles for the training and development of innovation skills. Methodology: This research is based on a combination of background research and direct survey of innovators, educators, scientists, and engineers, in addition to the general public. The survey is used to illuminate the nature of significant beliefs related to creativity and innovation practice. Contribution: We examine the myths and truths behind creativity as well as the false beliefs behind innovation as we present a closed model for innovation and the key framing elements needed to build a successful, trainable, developable system that is the innovation mindset. And like any skill, creativity and innovation can be taught and learned using tools and processes that can be followed, tracked, and documented. If innovation is a skill, creativity should not re-quire magic or the production of ideas out of thin air. Findings: This paper identifies the historic nature of creativity as well as the general strategies used by innovators in implementing innovation practices and pro-poses a framework that supports the effective development of the innovation mindset. Recommendations for Practitioners: Apply the framework and encourage ideation and innovation participants to appreciate that they can learn to be creative and innovative. Start as early as possible in the education process, as all of these skills can be instructed at early ages. Recommendations for Researchers: Continue to gather survey data to support a refined understanding of the motivations behind the disconnect between innovation as a methodical skill and the beliefs in the use of random ideation techniques. Impact on Society: Transforming the understanding of creativity and innovation from one of mythical belief to one of methodical skill application will dramatically alter the lifelong impact of knowledge gained in support of global economic and environmental challenges. Future Research: A continuation of the recommended research paths and collaboration with other creativity researchers leading to improved methods for dissuading mythical beliefs toward formalized, systematic ideation and innovation practices. *** NOTE: This Proceedings paper was revised and published in the journal Issues in Informing Science and Information Technology, 18, 83-102. Click DOWNLOAD PDF to download the published paper. ***
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Boukhris, Imen, Zied Elouedi, and Salem Benferhat. "Analyzing belief function networks with conditional beliefs." In 2011 11th International Conference on Intelligent Systems Design and Applications (ISDA). IEEE, 2011. http://dx.doi.org/10.1109/isda.2011.6121782.

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Lorini, Emiliano, and Francois Schwarzentruber. "Multi-Agent Belief Base Revision." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/270.

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We present a generalization of belief base revision to the multi-agent case. In our approach agents have belief bases containing both propositional beliefs and higher-order beliefs about their own beliefs and other agents’ beliefs. Moreover, their belief bases are split in two parts: the mutable part, whose elements may change under belief revision, and the core part, whose elements do not change. We study a belief revision operator inspired by the notion of screened revision. We provide complexity results of model checking for our approach as well as an optimal model checking algorithm. Moreover, we study complexity of epistemic planning formulated in the context of our framework.
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Baker, Clayton. "Predictive Modelling of Human Reasoning Using AGM Belief Revision." In Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. California: International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/811.

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While many forms of belief change exist, the relationship between belief revision and human reasoning is of primary interest in this work. The theory of belief revision extends classical two-valued logic with an approach to resolve the conflict between a set of beliefs and newly learned information. The goal of this project is to test how humans revise conflicting beliefs. Experiments are proposed in which human subjects are required to resolve conflicting beliefs via relevance and confidence. In our analysis, the human responses will be evaluated against the predictions of two perspectives of propositional belief revision: formal and psychological.
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Motamed, Nima, Natasha Alechina, Mehdi Dastani, and Dragan Doder. "Revising Beliefs and Intentions in Stochastic Environments." In Thirty-Third International Joint Conference on Artificial Intelligence {IJCAI-24}. California: International Joint Conferences on Artificial Intelligence Organization, 2024. http://dx.doi.org/10.24963/ijcai.2024/389.

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The development of autonomous agents operating in dynamic and stochastic environments requires theories and models of how beliefs and intentions are revised while taking their interplay into account. In this paper, we initiate the study of belief and intention revision in stochastic environments, where an agent's beliefs and intentions are specified in a decidable probabilistic temporal logic. We then provide general Katsuno & Mendelzon-style representation theorems for both belief and intention revision, giving clear semantic characterizations of revision methods.
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Hunter, Aaron, François Schwarzentruber, and Eric Tsang. "Belief Manipulation Through Propositional Announcements." In Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/154.

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Public announcements cause each agent in a group to modify their beliefs to incorporate some new piece of information, while simultaneously being aware that all other agents are doing the same. Given a set of agents and a set of epistemic goals, it is natural to ask if there is a single announcement that will make each agent believe the corresponding goal. This problem is known to be undecidable in a general modal setting, where the presence of nested beliefs can lead to complex dynamics. In this paper, we consider not necessarily truthful public announcements in the setting of AGM belief revision. We prove that announcement finding in this setting is not only decidable, but that it is simpler than the corresponding problem in the most simplified modal logics. We then describe AnnB, an implemented tool that uses announcement finding as the basis for controlling robot behaviour through belief manipulation.
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Feng, Yuzhang, Yuan Fang Li, Colin Keng-Yan Tan, Bimlesh Wadhwa, and Hai Wang. "Belief-augmented OWL (BOWL) Engineering the SemanticWeb with Beliefs." In 12th IEEE International Conference on Engineering Complex Computer Systems (ICECCS 2007). IEEE, 2007. http://dx.doi.org/10.1109/iceccs.2007.18.

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Haret, Adrian, and Stefan Woltran. "Belief Revision Operators with Varying Attitudes Towards Initial Beliefs." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/239.

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Classical axiomatizations of belief revision include a postulate stating that if new information is consistent with initial beliefs, then revision amounts to simply adding the new information to the original knowledge base. This postulate assumes a conservative attitude towards initial beliefs, in the sense that an agent faced with the need to revise them will seek to preserve initial beliefs as much as possible. In this work we look at operators that can assume different attitudes towards original beliefs. We provide axiomatizations of these operators by varying the aforementioned postulate and obtain representation results that characterize the new types of operators using preorders on possible worlds. We also present concrete examples for each new type of operator, adapting notions from decision theory.
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Reports on the topic "Beliefs"

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Andreoni, James, and Alison Sanchez. Do Beliefs Justify Actions or Do Actions Justify Beliefs? An Experiment on Stated Beliefs, Revealed Beliefs, and Social-Image Manipulation. Cambridge, MA: National Bureau of Economic Research, October 2014. http://dx.doi.org/10.3386/w20649.

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Heffetz, Ori, and Guy Ishai. Which Beliefs? Behavior-Predictive Beliefs are Inconsistent with Information-Based Beliefs: Evidence from COVID-19. Cambridge, MA: National Bureau of Economic Research, November 2021. http://dx.doi.org/10.3386/w29452.

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Bordalo, Pedro, Katherine Coffman, Nicola Gennaioli, and Andrei Shleifer. Beliefs about Gender. Cambridge, MA: National Bureau of Economic Research, December 2016. http://dx.doi.org/10.3386/w22972.

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Gandhi, Ashvin, Paola Giuliano, Eric Guan, Quinn Keefer, Chase McDonald, Michaela Pagel, and Joshua Tasoff. Beliefs that Entertain. Cambridge, MA: National Bureau of Economic Research, April 2024. http://dx.doi.org/10.3386/w32295.

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Goetzmann, William, Dasol Kim, and Robert Shiller. Crash Beliefs From Investor Surveys. Cambridge, MA: National Bureau of Economic Research, April 2016. http://dx.doi.org/10.3386/w22143.

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Thayer, Colette, and Erica Dinger. Healthy Lifestyle Beliefs vs. Behaviors. AARP Research, November 2016. http://dx.doi.org/10.26419/res.00139.001.

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Stawiski, Sarah, Jennifer Deal, and Bill Gentry. U.S. students’ beliefs about leadership. Center for Creative Leadership, 2014. http://dx.doi.org/10.35613/ccl.2014.2035.

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Tella, Rafael Di, and Juan Dubra. Peronist Beliefs and Interventionist Policies. Cambridge, MA: National Bureau of Economic Research, December 2010. http://dx.doi.org/10.3386/w16621.

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Xiong, Wei. Bubbles, Crises, and Heterogeneous Beliefs. Cambridge, MA: National Bureau of Economic Research, March 2013. http://dx.doi.org/10.3386/w18905.

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Chen, Xiaohong, Lars Hansen, and Peter Hansen. Robust Identification of Investor Beliefs. Cambridge, MA: National Bureau of Economic Research, May 2020. http://dx.doi.org/10.3386/w27257.

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