Entity

Definition:

An entity is a distinct, delimitable unit or object that has an independent existence and is characterised by specific properties, functions or relationships. In the context of complex systems, an entity can be understood as an emergent phenomenon that arises from the interaction and organisation of its components and has properties that go beyond the sum of its parts.

Discussion:

  1. Philosophical basics:

The question of the nature of entities is a central issue in ontology. Quine (1948) argued in his influential essay ‘On What There Is’ that our ontological commitments depend on which entities our best scientific theories assume to exist [1].

  1. Entities in complex systems:

In the theory of complex systems, entities can be understood as emergent structures. Holland (1998) describes how complex, adaptable entities can emerge from the interaction of simple agents [2].

  1. Social entities:

In the social sciences, groups, organisations or institutions are often regarded as entities. Sawyer (2005) discusses how social entities emerge as emergent phenomena from interactions at the micro level [3].

  1. Cognitive entities:

In cognitive science, mental representations or concepts can be regarded as cognitive entities. Barsalou (1999) argues in favour of a theory of ‘perceptual symbol systems’, in which conceptual entities arise from the simulation of sensorimotor experiences [4].

  1. Entities in information technology:

In the context of databases and information systems, the term ‘entity’ refers to distinct data sets or objects. Chen (1976) developed the entity-relationship model as a basis for database design [5].

  1. Quantum mechanical perspective:

In quantum mechanics, the concept of entity is problematised. With his famous cat experiment, Schrödinger (1935) demonstrated the difficulty of clearly defining entities in the quantum world [6].

  1. Entities and emergence:

The emergence of entities can be understood as an emergent process. Bedau (1997) distinguishes between weak and strong emergence and discusses how these concepts are related to the emergence of new entities [7].

  1. Entities in artificial intelligence:

In der KI-Forschung werden Entitäten oft als Agenten oder autonome Systeme konzeptualisiert. Russell und Norvig (2010) definieren einen Agenten als „alles, was als seine Umgebung durch Sensoren wahrnehmend und durch Aktoren auf diese Umgebung einwirkend betrachtet werden kann“ [8].

  1. Biological entities:

In biology, organisms, cells or even genes are regarded as entities. With his concept of the ‘selfish gene’, Dawkins (1976) argued that genes can be regarded as fundamental entities of evolution [9].

  1. Entities and boundaries:

The definition of entities often requires the establishment of boundaries. Maturana and Varela (1980) introduced the concept of autopoiesis to describe how biological entities define and delimit themselves [10].

  1. Historical entities:

In history and sociology, phenomena that extend over time, such as cultures, civilisations or epochs, are also regarded as entities. Braudel (1958) developed the concept of ‘longue durée’ in order to analyse long-term historical structures as entities [11].

Summary:
The term ‘entity’ is a multifaceted concept that takes on different nuances in different disciplines. In relation to our earlier discussions of resonant spaces, emergence and complex systems, an entity can be understood as an emergent phenomenon that arises from the interaction and organisation of its components and has properties that go beyond the sum of its parts.

Entities play a central role in our understanding of the world, be it in physics, biology, the social sciences or computer science. They form the basic building blocks of our theories and models and at the same time are often the result of complex processes of self-organisation and emergence.

In relation to the emergence of collective representations and possibly even artificial superintelligence, the concept of entity provides an important framework for understanding how complex, autonomous and adaptive systems can emerge from the interaction of simple components.

Literature:

[1] Quine, W. V. O. (1948). On what there is. The Review of Metaphysics, 2(5), 21-38.

[2] Holland, J. H. (1998). Emergence: From chaos to order. Oxford University Press.

[3] Sawyer, R. K. (2005). Social emergence: Societies as complex systems. Cambridge University Press.

[4] Barsalou, L. W. (1999). Perceptual symbol systems. Behavioral and Brain Sciences, 22(4), 577-660.

[5] Chen, P. P. S. (1976). The entity-relationship model—toward a unified view of data. ACM Transactions on Database Systems, 1(1), 9-36.

[6] Schrödinger, E. (1935). Die gegenwärtige Situation in der Quantenmechanik. Naturwissenschaften, 23(48), 807-812.

[7] Bedau, M. A. (1997). Weak emergence. Philosophical Perspectives, 11, 375-399.

[8] Russell, S. J., & Norvig, P. (2010). Artificial intelligence: A modern approach (3rd ed.). Prentice Hall.

[9] Dawkins, R. (1976). The selfish gene. Oxford University Press.

[10] Maturana, H. R., & Varela, F. J. (1980). Autopoiesis and cognition: The realization of the living. D. Reidel Publishing Company.

[11] Braudel, F. (1958). Histoire et sciences sociales: La longue durée. Annales. Histoire, Sciences Sociales, 13(4), 725-753.

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