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Learning identifiable representations and models from low-level observations is helpful for an intelligent spacecraft to complete downstream tasks reliably. For temporal observations, to ensure that the data generating process is provably…

Machine Learning · Computer Science 2024-12-05 Congxi Zhang , Yongchun Xie

Organisms have evolved immune systems that can counter pathogenic threats. The adaptive immune system in vertebrates consists of a diverse repertoire of immune receptors that can dynamically reorganize to specifically target the…

Populations and Evolution · Quantitative Biology 2024-10-29 Quinn N Bellamy , Zachary Montague , Luca Peliti , Armita Nourmohammad

Worm-inspired robots provide an effective locomotion strategy for constrained environments by combining cyclic body deformation with alternating anchoring. For compliant robots, however, the interaction between deformable anchoring…

Robotics · Computer Science 2026-04-15 Xinyu Zhou , Yu Mei , Faith Thomson , Christian Luedtke , Xinda Qi , Xiaobo Tan

With recent and rapid advancements in artificial intelligence (AI), understanding the foundation of purposeful behaviour in autonomous agents is crucial for developing safe and efficient systems. While artificial neural networks have…

Artificial Intelligence · Computer Science 2025-08-12 Aswin Paul , Moein Khajehnejad , Forough Habibollahi , Brett J. Kagan , Adeel Razi

Infants are experts at playing, with an amazing ability to generate novel structured behaviors in unstructured environments that lack clear extrinsic reward signals. We seek to mathematically formalize these abilities using a neural network…

Machine Learning · Computer Science 2018-11-01 Nick Haber , Damian Mrowca , Li Fei-Fei , Daniel L. K. Yamins

Introduction: Machine learning provides fundamental tools both for scientific research and for the development of technologies with significant impact on society. It provides methods that facilitate the discovery of regularities in data and…

Machine Learning · Computer Science 2019-03-12 Andrea Ceni , Peter Ashwin , Lorenzo Livi

Escape of active agents from metastable states is of great interest in statistical and biological physics. In this study, we investigate the escape of a flexible active ring, composed of active Brownian particles, from a flat attractive…

Soft Condensed Matter · Physics 2024-08-21 Bin Tang , Jin-cheng Gao , Kang Chen , Tian Hui Zhang , Wen-de Tian

Efficient exploration remains a challenging problem in reinforcement learning, especially for those tasks where rewards from environments are sparse. A commonly used approach for exploring such environments is to introduce some "intrinsic"…

Machine Learning · Computer Science 2020-07-16 Neale Ratzlaff , Qinxun Bai , Li Fuxin , Wei Xu

We study a random walk model in which the jumping probability to a site is dependent on the number of previous visits to the site, as a model of the mobility with memory. To this end we introduce two parameters called the memory parameter…

Physics and Society · Physics 2016-11-11 Jeehye Choi , Jang-Il Sohn , K. -I. Goh , I. -M. Kim

The dynamics of protection processes has been a fundamental challenge in systemic risk analysis. The conceptual principle and methodological techniques behind the mechanisms involved [in such dynamics] have been harder to grasp than…

Social and Information Networks · Computer Science 2019-07-29 Chulwook Park

The concept of emergence is a powerful concept to explain very complex behaviour by simple underling rules. Existing approaches of producing emergent collective behaviour have many limitations making them unable to account for the…

Multiagent Systems · Computer Science 2022-03-03 A. M. Khalili

Biological systems often choose actions without an explicit reward signal, a phenomenon known as intrinsic motivation. The computational principles underlying this behavior remain poorly understood. In this study, we investigate an…

Artificial Intelligence · Computer Science 2023-01-05 Stas Tiomkin , Ilya Nemenman , Daniel Polani , Naftali Tishby

In this paper we introduce a general estimation methodology for learning a model of human perception and control in a sensorimotor control task based upon a finite set of demonstrations. The model's structure consists of i the agent's…

Machine Learning · Computer Science 2025-05-02 Ran Wei , Anthony D. McDonald , Alfredo Garcia , Gustav Markkula , Johan Engstrom , Matthew O'Kelly

We present a novel approach to learn the formulae characterising the emergent behaviour of a dynamical system from system observations. At a high level, the approach starts by devising a statistical dynamical model of the system which…

Logic in Computer Science · Computer Science 2013-12-31 Ezio Bartocci , Luca Bortolussi , Guido Sanguinetti

C. elegans is the only animal for which a detailed neural connectivity diagram has been constructed. However, synaptic polarities in this diagram, and thus, circuit functions are largely unknown. Here, we deciphered the likely polarities of…

Neurons and Cognition · Quantitative Biology 2014-03-21 Franciszek Rakowski , Jagan Srinivasan , Paul W. Sternberg , Jan Karbowski

Can reproduction alone in the context of survival produce intelligence in our machines? In this work, self-replication is explored as a mechanism for the emergence of intelligent behavior in modern learning environments. By focusing purely…

Neural and Evolutionary Computing · Computer Science 2022-09-27 Samuel Schmidgall , Joseph Hays

The behaviours of a swarm are not explicitly engineered. Instead, they are an emergent consequence of the interactions of individual agents with each other and their environment. This emergent functionality poses a challenge to safety…

As pathogens spread in a population of hosts, immunity is built up and the pool of susceptible individuals is depleted. This generates selective pressure, to which many human RNA viruses, such as influenza virus or SARS-CoV-2, respond with…

Populations and Evolution · Quantitative Biology 2024-08-29 Pierre Barrat-Charlaix , Richard A. Neher

Human perceptual and cognitive abilities are limited resources. Today, in the age of cheap information --cheap to produce, to manipulate, to disseminate--, this cognitive bottleneck translates into hypercompetition for visibility among…

Data-driven discovery of emergent dynamics is gaining popularity, particularly in the context of reaction-diffusion systems. These systems are widely studied across various fields, including neuroscience, ecology, epidemiology, and several…