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It is proposed that the ability of humans to flourish in diverse environments and evolve complex cultures reflects the following two underlying cognitive transitions. The transition from the coarse-grained associative memory of Homo habilis to the fine-grained memory of Homo erectus enabled limited representational redescription of perceptually similar episodes, abstraction, and analytic thought, the last of which is modeled as the formation of states and of lattices of properties and contexts for concepts. The transition to the modern mind of Homo sapiens is proposed to have resulted from onset of the capacity to spontaneously and temporarily shift to an associative mode of thought conducive to interaction amongst seemingly disparate concepts, modeled as the forging of conjunctions resulting in states of entanglement. The fruits of associative thought became ingredients for analytic thought, and vice versa. The ratio of associative pathways to concepts surpassed a percolation threshold resulting in the emergence of a self-modifying, integrated internal model of the world, or worldview.

Abstract. Conceptual modelling is central to information systems development. The design of information systems requires appropriate languages to conceptualize interactions between actors. Mostly, design languages are adopted to the application system to be modelled instead of being aligned with the nature of perception of the modeller. Perception and cognition are very different from computations on symbolic representations. Cognitive structures and processes emerge from continous sensorimotor interactions. Action-oriented languages already consider action and coordination in terms of speech acts. However, speech acts can not be foundational as a speech act itself is brought forth or enacted in movement, in particular through action in perception. In this paper, it will be argued for non-representational modelling. To address the problems of representations, an ecological approach based on quantum interaction is proposed with respect to both criteria action in language and action in perception.

Abstract. According to recent studies in developmental psychology and neuroscience, symbolic language is essentially intersubjective. Empathetically relating to others renders possible the acquisition of linguistic constructs. Intersubjectivity develops in early ontogenetic life when interactions between mother and infant mutually shape their relatedness. Empirical findings suggest that the shared attention and intention involved in those interactions is sustained as it becomes internalized and embodied. Symbolic language is derivative and emerges from shared intentionality. In this paper, we present a formalization of shared intentionality based upon a quantum approach. From a phenomenological viewpoint, we investigate the nonseparable, dynamic and sustainable nature of social cognition and evaluate the appropriateness of quantum interaction for modelling intersubjectivity. 1

Abstract. The increasing availability of ontologies raises the need to establish relationships and make inferences across heterogeneous knowledge models. The approach proposed and supported by knowledge representation standards consists in establishing formal symbolic descriptions of a conceptualisation, which, it has been argued, lack grounding and are not expressive enough to allow to identify relations across separate ontologies. Ontology mapping approaches address this issue by exploiting structural or linguistic similarities between symbolic entities, which is costly, error-prone, and in most cases lack cognitive soundness. We argue that knowledge representation paradigms should have a better support for similarity and propose two distinct approaches to achieve it. We first present a representational approach which allows to ground symbolic ontologies by using Conceptual Spaces (CS), allowing for automated computation of similarities between instances across ontologies. An alternative approach is presented, which considers symbolic entities as contextual interpretations of processes in spacetime or Differences. By becoming a process of interpretation, symbols acquire the same status as other processes in the world and can be described (tagged) as well, which allows the bottom-up production of meaning. 1

Abstract. Space and time have not received much attention on the Semantic Web so far. While their importance has been recognized recently, existing work reduces them to simple latitude-longitude pairs and time stamps. In contrast, we argue that space and time are fundamental ordering relations for knowledge organization, representation, and reasoning. While most research on Semantic Web reasoning has focused on thematic aspects, this paper argues for a unified view combining a spatial, temporal, and thematic component. Besides their impact on the representation of and reasoning about individuals and classes, we outline the role of space and time for ontology modularization, evolution, and the handling of vague and contradictory knowledge. Instead of proposing yet another specific methodology, the presented work illustrates the relevance of space and time using various examples from the geo-sciences.

EVOC (for EVOlution of Culture) is a computer model of culture that enables us to investigate how various factors such as barriers to cultural diffusion, the presence and choice of leaders, or changes in the ratio of innovation to imitation affect the diversity and effectiveness of ideas. It consists of neural network based agents that invent ideas for actions, and imitate neighbors ’ actions. The model is based on a theory of culture according to which what evolves through culture is not memes or artifacts, but the internal models of the world that give rise to them, and they evolve not through a Darwinian process of competitive exclusion but a Lamarckian process involving exchange of innovation protocols. EVOC shows an increase in mean fitness of actions over time, and an increase and then decrease in the diversity of actions. Diversity of actions is positively correlated with population size and density, and with barriers between populations. Slowly eroding borders increase fitness without sacrificing diversity by fostering specialization followed by sharing of fit actions. Introducing a leader that broadcasts its actions throughout the population increases the fitness of actions but reduces diversity of actions. Increasing the number of leaders reduces this effect. Efforts are underway to simulate the conditions under which an agent immigrating from one culture to another contributes new ideas while still ‘fitting in’.

EVOC is a computer model of the EVOlution of Culture. It consists of neural network based agents that invent ideas for actions, and imitate neighbors ’ actions. EVOC replicates using a different fitness function the results obtained with an earlier model (MAV), including (1) an increase in mean fitness of actions, and (2) an increase and then decrease in the diversity of actions. Diversity of actions is positively correlated with number of needs, population size and density, and with the erosion of borders between populations. Slowly eroding borders maximize diversity, fostering specialization followed by sharing of fit actions. Square (as opposed to toroidal) worlds also exhibit higher diversity. Introducing a leader that broadcasts its actions throughout the population increases the fitness of actions but reduces diversity; these effects diminish the more leaders there are. Low density populations have less fit ideas but broadcasting diminishes this effect.

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and other research outputs Spatial groundings for meaningful symbols