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Introduction: In contrast to current AI technology, natural intelligence -- the kind of autonomous intelligence that is realized in the brains of animals and humans to attain in their natural environment goals defined by a repertoire of…

Artificial Intelligence · Computer Science 2022-05-03 Christoph von der Malsburg , Thilo Stadelmann , Benjamin F. Grewe

The origin and development of consciousness is poorly understood. Although it is clearly a naturalistic phenomenon evolved through Darwinian evolution, explaining it in terms of physicochemical, neural, or symbolic mechanisms remains…

Neurons and Cognition · Quantitative Biology 2014-10-20 J. H. van Hateren

Work in developmental psychology suggests that humans are predisposed to align their mental states with other individuals. This manifests principally in cooperative communication, that is, intentional communication geared towards aligning…

Neurons and Cognition · Quantitative Biology 2020-02-25 Jared Vasil , Paul B. Badcock , Axel Constant , Karl Friston , Maxwell J. D. Ramstead

We propose a new self-organizing mechanism behind the emergence of memory in which temporal sequences of stimuli are transformed into spatial activity patterns. In particular, the memory emerges despite the absence of temporal correlations…

Disordered Systems and Neural Networks · Physics 2009-11-07 Konstantin Klemm , Preben Alstrom

This article questions the widespread assumption that there are brain representations that will always remain unconscious in the sense of being inaccessible to individual awareness under any circumstances. This implies that some part of the…

Neurons and Cognition · Quantitative Biology 2022-02-23 Birgitta Dresp-Langley

Unlike robots, humans learn, adapt and perceive their bodies by interacting with the world. Discovering how the brain represents the body and generates actions is of major importance for robotics and artificial intelligence. Here we discuss…

Robotics · Computer Science 2021-05-11 Pablo Lanillos , Marcel van Gerven

Self-Modeling is the process by which an agent, such as an animal or machine, learns to create a predictive model of its own dynamics. Once captured, this self-model can then allow the agent to plan and evaluate various potential behaviors…

Robotics · Computer Science 2022-09-07 Robert Kwiatkowski , Yuhang Hu , Boyuan Chen , Hod Lipson

The brain can be considered as a system that dynamically optimizes the structure of anatomical connections based on the efficiency requirements of functional connectivity. To illustrate the power of this principle in organizing the…

Neurons and Cognition · Quantitative Biology 2024-02-07 Carlos Calvo Tapia , Valeriy A. Makarov Slizneva , Cees van Leeuwen

The evolutionary balance between innate and learned behaviors is highly intricate, and different organisms have found different solutions to this problem. We hypothesize that the emergence and exact form of learning behaviors is naturally…

Neurons and Cognition · Quantitative Biology 2023-03-14 Emmanouil Giannakakis , Sina Khajehabdollahi , Anna Levina

A remarkable feature of human beings is their capacity for creative behaviour, referring to their ability to react to problems in ways that are novel, surprising, and useful. Transformational creativity is a form of creativity where the…

Machine Learning · Computer Science 2019-06-26 Maarten Grachten , Carlos Eduardo Cancino Chacón

Living beings are able to solve a wide variety of problems that they encounter rarely or only once. Without the benefit of extensive and repeated experience with these problems, they can solve them in an ad-hoc manner. We call this capacity…

Artificial Intelligence · Computer Science 2025-07-17 Alex Baranski , Jun Tani

We explore how physical scale and population size shape the emergence of complex behaviors in open-ended ecological environments. In our setting, agents are unsupervised and have no explicit rewards or learning objectives but instead evolve…

Autonomous robots need to be able to adapt to unforeseen situations and to acquire new skills through trial and error. Reinforcement learning in principle offers a suitable methodological framework for this kind of autonomous learning.…

Robotics · Computer Science 2016-08-02 Nikolas J. Hemion

Living organisms process information to interact and adapt to their changing environment with the goal of finding food, mates or averting hazards. The structure of their niche has profound repercussions by both selecting their internal…

Physics and Society · Physics 2017-06-07 Hannes Hornischer , Stephan Herminghaus , Marco G. Mazza

One of the defining features of living systems is their adaptability to changing environmental conditions. This requires organisms to extract temporal and spatial features of their environment, and use that information to compute the…

Neurons and Cognition · Quantitative Biology 2024-02-27 Maria Sol Vidal-Saez , Oscar Vilarroya , Jordi Garcia-Ojalvo

Animals behave adaptively in the environment with multiply competing goals. Understanding of the mechanisms underlying such goal-directed behavior remains a challenge for neuroscience as well for adaptive system research. To address this…

Neural and Evolutionary Computing · Computer Science 2012-04-17 Konstantin Lakhman , Mikhail Burtsev

We have designed a machine that becomes increasingly better at behaving in underspecified circumstances, in a goal-directed way, on the job, by modeling itself and its environment as experience accumulates. Based on principles of…

The fields of Origin of Life and Artificial Life both question what life is and how it emerges from a distinct set of "pre-life" dynamics. One common feature of most substrates where life emerges is a marked shift in dynamics when…

Neural and Evolutionary Computing · Computer Science 2024-08-05 Blaise Agüera y Arcas , Jyrki Alakuijala , James Evans , Ben Laurie , Alexander Mordvintsev , Eyvind Niklasson , Ettore Randazzo , Luca Versari

Developing autonomous agents that quickly explore an environment and adapt their behavior online is a canonical challenge in robotics and machine learning. While humans are able to achieve such fast online exploration and adaptation, often…

Machine Learning · Computer Science 2025-07-15 Andrew Wagenmaker , Zhiyuan Zhou , Sergey Levine

When viewed at a certain coarse grain, the brain seems a relatively small dynamical system composed by a few dozen interacting areas, performing a number of stereotypical behaviors. It is known that, even relatively small dynamical systems…

Neurons and Cognition · Quantitative Biology 2015-06-26 Dante R. Chialvo