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Much has been debated about the benefit of sexual over asexual reproduction in terms of evolutionary fitness. Here we focus on the advantage that may be brought about by the process of mating, where the choosing of mates contributes to the…
Like a rocket being propelled into space, evolution has engineered flies to launch into adulthood via multiple stages. Flies develop and deploy two distinct bodies, linked by the transformative process of metamorphosis. The fly larva is a…
The scheme of a unified Darwinian evolutionary theory for physical and biological systems is described. Every physical system is methodologically endowed with a classical information processor what turns every system into an agent being…
This paper argues that Machine Learning (ML) algorithms must be educated. ML-trained algorithms moral decisions are ubiquitous in human society. Sometimes reverting the societal advances governments, NGOs and civil society have achieved…
The ocean vast unexplored regions and diverse soft-bodied marine organisms have spurred interest in bio-inspired underwater soft robotics. Recent advances have enabled new capabilities in underwater movement, sensing, and interaction.…
Modularisation, repetition, and symmetry are structural features shared by almost all biological neural networks. These features are very unlikely to be found by the means of structural evolution of artificial neural networks. This paper…
We present a comprehensive framework for studying and leveraging morphological symmetries in robotic systems. These are intrinsic properties of the robot's morphology, frequently observed in animal biology and robotics, which stem from the…
Robots that can execute various tasks automatically on behalf of humans are becoming an increasingly important focus of research in the field of robotics. Imitation learning has been studied as an efficient and high-performance method, and…
Developing a framework for the locomotion of a six-legged robot or a hexapod is a complex task that has extensive hardware and computational requirements. In this paper, we present a bio-inspired framework for the locomotion of a hexapod.…
Backpropagation-optimized artificial neural networks, while precise, lack robustness, leading to unforeseen behaviors that affect their safety. Biological neural systems do solve some of these issues already. Unlike artificial models,…
Convolutional neural networks belong to the most successul image classifiers, but the adaptation of their network architecture to a particular problem is computationally expensive. We show that an evolutionary algorithm saves training time…
While the original goal for developing robots is replacing humans in dangerous and tedious tasks, the final target shall be completely mimicking the human cognitive and motor behaviour. Hence, building detailed computational models for the…
Learning companion robots for young children are increasingly adopted in informal learning environments. Although parents play a pivotal role in their children's learning, very little is known about how parents prefer to incorporate robots…
Learning to interact with the environment not only empowers the agent with manipulation capability but also generates information to facilitate building of action understanding and imitation capabilities. This seems to be a strategy adopted…
The evolutionary process has been modelled in many ways using both stochastic and deterministic models. We develop an algebraic model of evolution in a population of asexually reproducing organisms in which we represent a stochastic walk in…
We analyze a stylized model of co-evolution between any two purely competing species (e.g., host and parasite), both sexually reproducing. Similarly to a recent model of Livnat \etal~\cite{evolfocs14} the fitness of an individual depends on…
Which kind of complex behavior may arise from self-organizing principles? We investigate this question for the case of snake-like robots composed of passively coupled segments, with every segment containing two wheels actuated separately by…
Designing controllers for robot swarms is challenging, because human developers have typically no good understanding of the link between the details of a controller that governs individual robots and the swarm behavior that is an indirect…
Creating autonomous robots that can actively explore the environment, acquire knowledge and learn skills continuously is the ultimate achievement envisioned in cognitive and developmental robotics. Their learning processes should be based…
We try to perform geometrization of psychology by representing mental states, <<ideas>>, by points of a metric space, <<mental space>>. Evolution of ideas is described by dynamical systems in metric mental space. We apply the mental space…