First Steps Towards an Ontology of Belief

Logic and Logical Philosophy, 2004

There have been attempts to get some logic out of belief dynamics, i.e. attempts to define the constants of propositional logic in terms of functions from sets of beliefs to sets of beliefs. 1 It would be interesting to see whether something similar could be done for ontological categories, i.e. ontological constants. The theory presented here will be a (modest) expansion of belief dynamics: it will not only incorporate beliefs, but also parts of beliefs, so called belief fragments. On the basis of this we will give a belief-dynamical account of the ontological categories of states of affairs, individuals, properties of arbitrary adicities and properties of arbitrary orders.

International Journal of Human-Computer Studies, 2007

In this paper we explore the use of a formal ontology as a constraining framework for the belief store of a rational agent. The static beliefs of the agent are the axioms of the ontology. The dynamic beliefs are the descriptions of the individuals that are instances of the ontology classes. The individuals all have a unique identifier, an associated set of named classes to which they are believed to belong, and a set of property values. The ontology axioms act as a schema for the dynamic beliefs. Belief updates not conforming to the axioms lead to either rejection of the update or some other revision of the dynamic belief store to maintain consistency. Partial descriptions are augmented by inferences of property values and class memberships licensed by the axioms. For concreteness we sketch how such an ontology based agent belief store could be implemented in a multi-threaded logic programming language with action rules and object oriented programming features called Go!. This language was specifically designed for implementing communicating rational agent applications. We shall see that its logic rules allow us to extend an ontology of classes and properties with rule defined n-ary relations and functions. Its action rules enable us to implement a consistency maintenance system that takes into account justifications for beliefs. The pragmatics of consistency maintenance is an issue not normally considered by the ontology community. The paper assumes some familiarity with ontology specification using languages such as OWL DL and its subsets, and with logic programming.

Computational Intelligence, 1995

The epistemic notions of knowledge and belief have most commonly been modeled by means of possible worlds semantics. In such approaches an agent knows (or believes) all logical consequences of its beliefs. Consequently, several approaches have been proposed to model systems of explicit belief, more suited to modeling finite agents or computers. In this paper a general framework is developed for the specification of logics of explicit belief. A generalization of possible worlds, called situations, is adopted. However the notion of an accessibility relation is not employed; instead a sentence is believed if the explicit proposition expressed by the sentence appears among a set of propositions associated with an agent at a situation. Since explicit propositions may be taken as corresponding to "belief contexts" or "frames of mind," the framework also provides a setting for investigating such approaches to belief. The approach provides a uniform and flexible basis from which various issues of explicit belief may be addressed and from which systems may be contrasted and compared. A family of logics is developed using this framework, which extends previous approaches and addresses issues raised by these earlier approaches. The more interesting of these logics are tractable, in that determining if a belief follows from a set of beliefs, given certain assumptions, can be accomplished in polynomial time.

Logic and Logical Philosophy Volume 10 (2002), 199–210, 2002

There have been attempts to get some logic out of belief dynamics, i.e. attempts to define the constants of propositional logic in terms of functions from sets of beliefs to sets of beliefs. It would be interesting to see whether something similar could be done for ontological categories, i.e. ontological constants. The theory presented here will be a (modest) expansion of belief dynamics: it will not only incorporate beliefs, but also parts of beliefs, so called belief fragments. On the basis of this we will give a belief-dynamical account of the ontological categories of states of affairs, individuals, properties of arbitrary adicities and properties of arbitrary orders.

Formal Ontology in Information Systems, 2018

 Discussion on BFO list 11/17  Relevance of faith-related concepts in human culture  Impact on well-being, health, social behaviour  Interest in developing a framework for terms of controversial reference in a realist ontology [1,2] , using a simple logic (OWL-DL)  If this can be shown for religion / spirituality: blueprint for other domains: fiction, law, history, philosophy  Preliminary work Robert Rovetto: Q1: Would bfo be inclusive of God, Soul, Spirit, etc.? Q2: Does (or would) bfo exclude them (and if so why)? Q3: If a user wants to include terms for God, Spirit, Soul, etc., how would they do so in bfo? Q4: Would bfo be able to correctly characterize them according to the view of the user?

Journal of Applied Logics, 2020

Recently there have been numerous proposed solutions to the problem of logical omniscience in doxastic and epistemic logic. Though these solutions display an impressive breadth of subtlety and motivation, the crux of these approaches seems to have a common theme-minor revisions around the ubiquitous Kripke semantics-rooted approach. In addition, the psychological mechanisms at work in and around both belief and knowledge have been left largely untouched. In this paper, we cut straight to the core of the problem of logical omniscience, taking a psychologically-rooted approach, taking as bedrock the "quanta" of given percepts, qualia and cognitions, terming our approach "PQG logic", short for percept, qualia, cognition logic. Building atop these quanta, we reach a novel semantics of belief, knowledge, in addition to a semantics for psychological necessity and possibility. With these notions we are well-equipped to not only address the problem of logical omniscience but to more deeply investigate the psychical-logical nature of belief and knowledge.

Artificial Intelligence: Methodology, …, 1998

One of the most interesting puzzles in formalizing belief contexts is the fact that many belief reports can be given both an opaque and a transparent readings. A traditional explanation is that the two readings are related to the failure and success of the principle of substitutivity respectively, and this in turn is explained with the de re/de dicto distinction. We propose an alternative analysis, based on the idea that another agent's beliefs can just be quoted (preserving opacity) or translated into the reporter's language (allowing for transparency). We show that MultiContext systems allow for the formalization of these two phenomena at the same time, thanks to their multi-language feature.

Journal of Philosophical Logic, 1993

Intentions are an important concept in Artificial Intelligence and Cognitive Science. We present a formal theory of intentions and beliefs based on Discourse Representation Theory that captures many of their important logical properties. Unlike possible worlds approaches, this theory does not assume that agents are perfect reasoners, and gives a realistic view of their internal architecture; unlike most representational approaches, it has anobjective semantics, and does not rely on anad hoc labeling of the internal states of agents. We describe a minimal logic for intentions and beliefs that is sound and complete relative to our semantics. We discuss several additional axioms, and the constraints on the models that validate them.

2004

ABSTRACT Collaboration, especially knowledge sharing, enables the advance of science as well as human society. In cyberspace, socializing the traditionally isolated intelligent software agents is an ultimate goal of the emerging Semantic Web activity. When making collaboration decisions, an agent usually needs explicitly represented facts about the agent world, such as “who knows what” and “who can do what”.

Proceedings of the Sixth Congress of the European Society for Research in Mathematics Education, January 28th - February 1st 2009, Lyon, France, 2010

In this paper I analyze different existing definitions of the term beliefs, focusing on relations between beliefs and knowledge. Through this analysis I note several problems with different types of definitions. In particular, when defining beliefs through a distinction between belief and knowledge systems, this creates an idealized view of knowledge, seen as something more pure (less affective, less episodic, and more logical). In addition, attention is generally not given to from what point of perspective a definition is made; if the distinction between beliefs and knowledge is seen as being either individual/psychological or social. These two perspectives are also sometimes mixed, which results in a messy construct. Based on the performed analysis, a conceptualization of beliefs is suggested.

2000

2021

Beliefs are, or at least appear to be, integral to cognition and action. Though there are scarcely features of human psychology more intuitive to their bearers, beliefs are surprisingly elusive targets of study. In this chapter, we consider some perennial questions about beliefs and suggest that some clarity might be achieved by viewing beliefs through the lens of cognitive psychology. We discuss psychological findings and evolutionary considerations which seem to imply that the mind is not designed to form true beliefs, but beliefs that are instrumentally useful. This issue is redolent of debates over whether people are rational or irrational and whether beliefs aim at truth or serve other psychological functions. We survey a series of practical tradeoffs and computational constraints that limit the attainment of true beliefs, and which may be responsible for apparent irrationality. Additionally, the origin of false or irrational-seeming beliefs may be inadequately specified by beh...

Frontiers in Psychology, 2022

The nature of beliefs Conceptualizations of beliefs differ according to the school of thought considered; here, we take the view from cognitive science. In cognitive science, beliefs are propositional attitudes, where the world is depicted as being in some state or another (Schwitzgebel, 2021). Beliefs have two main properties: some representational content and assumed veracity (Stephens and Graham, 2004). Beliefs entail specific representational content, which portrays causes of sensations (agency, events, and objects) as being a specific way (Rimell, 2021). So understood, they are undoubtedly a central part of cognition, dictating our perceptions, behavior, and executive functions. Beliefs do not need to be conscious or linguistically articulated, and indeed, the majority of beliefs can be construed as subpersonal; i.e., remain unconscious (Majeed, 2022). Rational agents generally view beliefs as having a truth value, and update their beliefs in light of new evidence. The term "belief " is also used to denote a more deflationary sense, where what is at stake is merely a probability density over some support; where we call a belief a probabilistic assessment of how plausible some state of affairs is (Smets, 2005). On this probabilistic reading, beliefs acquire the attribute of uncertainty-or its complement precision. Beliefs provide the foundation that allows agents to understand-or at least make sense of-the world and act within it: they provide agents with a consistent and coherent representation of their world, which they can then use to make inferences about the causal structure of the world and their place within it (Churchland and Churchland, 2013). This scaffolding of beliefs helps [human] agents appraise the environment, explain new observations, construct shared perspectives on the world, and engage in goal-directed behavior. Beliefs also help us experience the world temporally, as they can represent the state of the world in the past and allow us to anticipate its state in the future; this is especially important when holding beliefs about the consequences of action-a prerequisite for planning and a sense of agency (Shipp et al., 2009). Active inference Active inference is a formal description of self-organization derived from the variational free energy principle, and provides a mechanistic account of belief-guided