Grasping What? Ecological Anchors for Abstract Thought

2021 ◽  
pp. 1-6
Author(s):  
Harry Heft
Keyword(s):  
2020 ◽  
Author(s):  
Luca Rade

Emulators are internal models, first evolved for prediction in perception to shorten the feedback on motor action. However, the selective pressure on perception is to improve the fitness of decision-making, driving the evolution of emulators towards context-dependent payoff representation and integration of action planning, not enhanced prediction as is generally assumed. The result is integrated perceptual, memory, representational, and imaginative capacities processing external input and stored internal input for decision-making, while simultaneously updating stored information. Perception, recall, imagination, theory of mind, and dreaming are the same process with different inputs. Learning proceeds via scaffolding on existing conceptual infrastructure, a weak form of embodied cognition. Discrete concepts are emergent from continuous dynamics and are in a perceptual, not representational, format. Language is also in perceptual format and enables precise abstract thought. In sum, what was initially a primitive system for short-term prediction in perception has evolved to perform abstract thought, store and retrieve memory, understand others, hold embedded action plans, build stable narratives, simulate scenarios, and integrate context dependence into perception. Crucially, emulators co-evolved with the emergence of societies, producing a mind-society system in which emulators are dysfunctional unless integrated into a society, which enables their complexity. The Target Emulator System, evolved initially for honest signaling, produces the emergent dynamics of the mind-society system and spreads variation-testing of behavior and thought patterns across a population. The human brain is the most dysfunctional in isolation, but the most effective given its context.


Author(s):  
Torbjörn Tännsjö

The three most promising theories of distributive ethics are presented: Utilitarianism, with or without a prioritarian amendment. The maximin/leximin theory. Egalitarianism. Utilitarianism urges us to maximize the sum-total of happiness. When prioritarianism is added to utilitarianism we are instead urged to maximize a weighted sum of happiness, where happiness weighs less the happier you are and unhappiness weighs more the more miserable you are. The maximin/leximin theory urges us to give absolute priority to those who are worst off. Egalitarianism gives us two goals: to maximize happiness but also to level out differences with regard to happiness between persons. All of these theories are justifiable. In abstract thought experiments they conflict. When applied in real life they converge in an unexpected manner: more resources should be directed to mental health and less to marginal life extension. It is doubtful if the desired change will take place, however. What gets in its way is human irrationality.


Polar Record ◽  
1982 ◽  
Vol 21 (130) ◽  
pp. 23-32 ◽  
Author(s):  
Jørgen Taagholt

Throughout their history Greenlanders have struggled not against invaders but against a hard and merciless environment. This intimate association with the environment is reflected in a well-developed descriptive language, richer in many respects than Danish. But Greenlanders have a less developed capacity for abstract thought and as a result they find discussion of such national problems as security far removed from the daily debate. In diis article Greenland's development is traced and her strategic position in the North Atlantic is discussed in terms of national interests and international cooperation.


2006 ◽  
Vol 38 (1) ◽  
pp. 45-59
Author(s):  
Zora Krnjaic

The paper starts from the assumption that expert thinking is a complex manner of thinking of higher order, comprising higher mental functions and complex capabilities based on deep structures and knowledge patterns. It is a domain-determined and specialized thinking developed through systematic education. Particular aspects of ability, selected for this study, primarily concern the relation between abilities and knowledge and the relation between general and specific abilities. Particular emphasis was laid on the key concepts of the theories presented, relevant for the study of the complex nature of expert thinking. Special attention was paid to mediated intelligence and the process of systemogenesis of knowledge, Katel?s definition of crystallized intelligence, Gardener?s work on multiple intelligences in the context of knowledge and experience as well as Sternberg?s two-facet subtheory. The capability for abstract thought and the ability to select what is important as well as the domain of relevant specific capability are assumed to be of special relevance for understanding expert thinking and, as such, they were articulated and examined. Expert thinking-abstract, specialized and domain-specific, seems to be based on general and specific capabilities and their interaction.


2021 ◽  
Author(s):  
Liane Gabora ◽  
Nicole Beckage

Reflexively Autocatalytic Foodset-generated (RAF) networks have been used to model the origins of evolutionary processes, both biological (the origin of life) and cultural (the origin of cumulative innovation). The RAF approach tags conceptual shifts with their source, making it uniquely suited to modelling how new ideas grow out of currently available knowledge, studying order effects, and tracking conceptual trajectories within (and across) individuals. Using RAF networks, we develop a step-by-step process model of conceptual change (i.e., the process by which a child becomes an active participant in cultural evolution), focusing on childrens’ mental models of the shape of the earth. Using results from (Vosniadou & Brewer, 1992), we model different trajectories from the flat earth model to the spherical earth model, as well as the impact of other factors, such as pretend play, on cognitive development. As RAFs increase in size and number, they begin to merge and form a maxRAF that bridges previously compartmentalized knowledge. The expanding maxRAF constrains and enables the scaffolding of new conceptual structure. Once most conceptual structure is subsumed by the maxRAF, the child can reliably frame new knowledge and experiences in terms of previous knowledge and experiences, and engage in recursive representational redescription, or abstract thought, at which point the conceptual network becomes a self-organizing structure. The approach distinguishes between mental representations acquired through social learning or individual learning (of existing information), and mental representations obtained through abstract thought (resulting in the generation of new information). We suggest that individual differences in reliance on these information sources culminates in different kinds of conceptual networks and concomitant learning trajectories. These differences may be amplified by differences in the proclivity to spontaneously tailor one’s mode of thought to the situation one is in by modulating the degree of divergence (versus convergence), abstractness (versus concreteness), and context-specificity. We discuss a potential role for the approach in the development of an overarching framework that integrates evolutionary and developmental approaches to cognition.


Author(s):  
Anna Ursyn

“Visual Tweet: nature inspired visual statements” explores connections between science, computing, and art in a similar way as it is done in the previous chapter, “Looking at sciences through the water.” This chapter examines concepts and processes that relate to some fields in physics, biology, computing, and other sciences, and at the same time pertain to the planet’s life and humanity’s everyday experience. This chapter solves the projects visually, through art and/or graphics. Exploration of science-based concepts and nature-related processes support the understanding of the project themes, triggers imagination, and thus inspires enhancements to the ability to communicate with visual language and create artistic work. Comprehension of what is observed, the power of abstract thought, and an answer to evolving issues will result in personal visual projects – drawings, graphics, illustrations, animations, video clips, or web projects. This chapter comprises two projects about science-related themes: (1) Symmetry and pattern in animal world: geometry and art, and (2) Crystals and crystal caves. Each project invites the reader to create visual presentation of this theme.


Author(s):  
Murugan Sethuraman Sethuraman

AI has been defined in different ways, including the abilities for abstract thought, understanding, communication, reasoning, learning, retaining, planning, and solving. Intelligence is most widely studied in humans, but has also been observed in animals and plants. AI is the intelligence of machines or the simulation of intelligence in machines. AI is both the intelligence of machines and the branch of Computer Science which aims to create it, through the study and design of intelligent agents or rational agents, where an intelligent agent is a system that perceives its environment and takes actions which maximize its chances of success. Achievements include constrained and well-defined problems such as games, crossword-solving and optical character recognition. Among the traits that researchers hope machines will exhibit are reasoning, knowledge, planning, learning, communication, perception, and the ability to move and manipulate objects. In the field of AI there is no consensus on how closely the brain should be simulated.


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