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Machine intelligence can develop either directly from experience or by inheriting experience through evolution. The bulk of current research efforts focus on algorithms which learn directly from experience. I argue that the alternative,…

Neural and Evolutionary Computing · Computer Science 2021-06-22 Awni Hannun

Trustworthy Artificial Intelligence (AI) is based on seven technical requirements sustained over three main pillars that should be met throughout the system's entire life cycle: it should be (1) lawful, (2) ethical, and (3) robust, both…

In evolutionary robotics, jointly optimising the design and the controller of robots is a challenging task due to the huge complexity of the solution space formed by the possible combinations of body and controller. We focus on the…

Robotics · Computer Science 2024-03-18 Léni K. Le Goff , Edgar Buchanan , Emma Hart

One of the main properties of biological systems is modularity, which manifests itself at all levels of their organization, starting with the level of molecular genetics, ending with the level of whole organisms and their communities. In a…

Neural and Evolutionary Computing · Computer Science 2018-11-20 Anton Eremeev , Alexander Spirov

It is argued that selection criteria usually referred to as "anthropic conditions" for the existence of intelligent (typical) observers widely adopted in cosmology amount only to preconditions for primitive life. The existence of life does…

High Energy Physics - Theory · Physics 2015-05-18 Marcelo Gleiser

The concept of (auto)catalytic systems has become a cornerstone in understanding evolutionary processes in various fields. The common ground is the observation that for the production of new species/goods/ideas/elements etc. the…

Populations and Evolution · Quantitative Biology 2009-11-13 Rudolf Hanel , Peter Klimek , Stefan Thurner

Open-ended evolution requires unbounded possibilities that evolving entities can explore. The cardinality of a set of those possibilities thus has a significant implication for the open-endedness of evolution. We propose that facilitating…

Neural and Evolutionary Computing · Computer Science 2019-02-04 Hiroki Sayama

The process of evolutionary diversification unfolds in a vast genotypic space of potential outcomes. During the past century there have been remarkable advances in the development of theory for this diversification, and the theory's success…

Populations and Evolution · Quantitative Biology 2011-10-14 Troy Day

Biological networks have evolved to be highly functional within uncertain environments while remaining extremely adaptable. One of the main contributors to the robustness and evolvability of biological networks is believed to be their…

Molecular Networks · Quantitative Biology 2008-02-14 Arend Hintze , Christoph Adami

This paper presents an evolutionary algorithm with a new goal-sequence domination scheme for better decision support in multi-objective optimization. The approach allows the inclusion of advanced hard/soft priority and constraint…

Artificial Intelligence · Computer Science 2011-06-02 E. F. Khor , T. H. Lee , R. Sathikannan , K. C. Tan

The long-term behaviour of dynamic systems can be classified in two different regimes, regular or chaotic, depending on the values of the control parameters, which are kept constant during the time evolution. Starting from slightly…

Condensed Matter · Physics 2007-05-23 Paulo Murilo Castro de Oliveira

The study of the physical properties of open quantum systems is at the heart of many present investigations which aim to describe their dynamical evolution, on theoretical ground and through physical realizations. Here we develop a…

Quantum Physics · Physics 2021-11-23 Tarek Khalil , Jean Richert

Many socio-economic and biological processes can be modeled as systems of interacting individuals. The behaviour of such systems can be often described within game-theoretic models. In these lecture notes, we introduce fundamental concepts…

Populations and Evolution · Quantitative Biology 2013-05-30 Jacek Miekisz

The interaction networks of biological systems are known to take on several non-random structural properties, some of which are believed to positively influence system robustness. Researchers are only starting to understand how these…

Neural and Evolutionary Computing · Computer Science 2011-02-08 James M. Whitacre , Ruhul A. Sarker , Q. Tuan Pham

The continuity of life and its evolution, we proposed, emerge from an interactive group process manifested in networks of interaction. We term this process \textit{survival-of-the-fitted}. Here, we reason that survival of the fitted results…

Neural and Evolutionary Computing · Computer Science 2025-06-17 Irun R. Cohen , Assaf Marron

Building software-driven systems that are easily understood becomes a challenge, with their ever-increasing complexity and autonomy. Accordingly, recent research efforts strive to aid in designing explainable systems. Nevertheless, a common…

Artificial Intelligence · Computer Science 2019-02-11 Dimitri Bohlender , Maximilian A. Köhl

Our planet is experiencing an accelerated process of change associated to a variety of anthropogenic phenomena. The future of this transformation is uncertain, but there is general agreement about its negative unfolding that might threaten…

Adaptation and Self-Organizing Systems · Physics 2014-11-24 Ricard Solé

Many biological processes can be thought of as the result of an underlying dynamics in which the system repeatedly undergoes distinct and abortive trajectories with the dynamical process only ending when some specific process, purpose,…

Biological Physics · Physics 2025-06-05 Jane Kondev , Marc Kirschner , Hernan G. Garcia , Gabriel L. Salmon , Rob Phillips

Evolution is the theory that plants and animals today have come from kinds that have existed in the past. Scientists such as Charles Darwin and Alfred Wallace dedicate their life to observe how species interact with their environment, grow,…

Neural and Evolutionary Computing · Computer Science 2022-09-16 Manasa Josyula

Machine learning has achieved remarkable success in many applications. However, existing studies are largely based on the closed-world assumption, which assumes that the environment is stationary, and the model is fixed once deployed. In…

Machine Learning · Computer Science 2025-06-24 Fei Zhu , Shijie Ma , Zhen Cheng , Xu-Yao Zhang , Zhaoxiang Zhang , Dacheng Tao , Cheng-Lin Liu