2,366 research outputs found
The Emergence of Canalization and Evolvability in an Open-Ended, Interactive Evolutionary System
Natural evolution has produced a tremendous diversity of functional
organisms. Many believe an essential component of this process was the
evolution of evolvability, whereby evolution speeds up its ability to innovate
by generating a more adaptive pool of offspring. One hypothesized mechanism for
evolvability is developmental canalization, wherein certain dimensions of
variation become more likely to be traversed and others are prevented from
being explored (e.g. offspring tend to have similarly sized legs, and mutations
affect the length of both legs, not each leg individually). While ubiquitous in
nature, canalization almost never evolves in computational simulations of
evolution. Not only does that deprive us of in silico models in which to study
the evolution of evolvability, but it also raises the question of which
conditions give rise to this form of evolvability. Answering this question
would shed light on why such evolvability emerged naturally and could
accelerate engineering efforts to harness evolution to solve important
engineering challenges. In this paper we reveal a unique system in which
canalization did emerge in computational evolution. We document that genomes
entrench certain dimensions of variation that were frequently explored during
their evolutionary history. The genetic representation of these organisms also
evolved to be highly modular and hierarchical, and we show that these
organizational properties correlate with increased fitness. Interestingly, the
type of computational evolutionary experiment that produced this evolvability
was very different from traditional digital evolution in that there was no
objective, suggesting that open-ended, divergent evolutionary processes may be
necessary for the evolution of evolvability.Comment: SI can be found at: http://www.evolvingai.org/files/SI_0.zi
Adaptive modular architectures for rich motor skills: technical report on the cognitive architecture
Towards the integration of modern power systems into a cyber–physical framework
The cyber–physical system (CPS) architecture provides a novel framework for analyzing and expanding research and innovation results that are essential in managing, controlling and operating complex, large scale, industrial systems under a holistic insight. Power systems constitute such characteristically large industrial structures. The main challenge in deploying a power system as a CPS lies on how to combine and incorporate multi-disciplinary, core, and advanced technologies into the specific for this case, social, environmental, economic and engineering aspects. In order to substantially contribute towards this target, in this paper, a specific CPS scheme that clearly describes how a dedicated cyber layer is deployed to manage and interact with comprehensive multiple physical layers, like those found in a large-scale modern power system architecture, is proposed. In particular, the measurement, communication, computation, control mechanisms, and tools installed at different hierarchical frames that are required to consider and modulate the social/environmental necessities, as well as the electricity market management, the regulation of the electric grid, and the power injection/absorption of the controlled main devices and distributed energy resources, are all incorporated in a common CPS framework. Furthermore, a methodology for investigating and analyzing the dynamics of different levels of the CPS architecture (including physical devices, electricity and communication networks to market, and environmental and social mechanisms) is provided together with the necessary modelling tools and assumptions made in order to close the loop between the physical and the cyber layers. An example of a real-world industrial micro-grid that describes the main aspects of the proposed CPS-based design for modern electricity grids is also presented at the end of the paper to further explain and visualize the proposed framework
Exploring the Modularity and Structure of Robots Evolved in Multiple Environments
Traditional techniques for the design of robots require human engineers to plan every aspect of the system, from body to controller. In contrast, the field of evolu- tionary robotics uses evolutionary algorithms to create optimized morphologies and neural controllers with minimal human intervention. In order to expand the capability of an evolved agent, it must be exposed to a variety of conditions and environments.
This thesis investigates the design and benefits of virtual robots which can reflect the structure and modularity in the world around them. I show that when a robot’s morphology and controller enable it to perceive each environment as a collection of independent components, rather than a monolithic entity, evolution only needs to optimize on a subset of environments in order to maintain performance in the overall larger environmental space. I explore previously unused methods in evolutionary robotics to aid in the evolution of modularity, including using morphological and neurological cost.
I utilize a tree morphology which makes my results generalizable to other mor- phologies while also allowing in depth theoretical analysis about the properties rel- evant to modularity in embodied agents. In order to better frame the question of modularity in an embodied context, I provide novel definitions of morphological and neurological modularity as well as create the sub-goal interference metric which mea- sures how much independence a robot exhibits with regards to environmental stimu- lus.
My work extends beyond evolutionary robotics and can be applied to the opti- mization of embodied systems in general as well as provides insight into the evolution of form in biological organisms
Incentives and co-evolution: Steering linear dynamical systems with noncooperative agents
Modern socio-technical systems typically consist of many interconnected users
and competing service providers, where notions like market equilibrium are
tightly connected to the ``evolution'' of the network of users. In this paper,
we model the users' dynamics as a linear dynamical system, and the service
providers as agents taking part to a generalized Nash game, whose outcome
coincides with the input of the users' dynamics. We thus characterize the
notion of co-evolution of the market and the network dynamics and derive
dissipativity-based conditions leading to a pertinent notion of equilibrium. We
then focus on the control design and adopt the light-touch policy to
incentivize or penalize the service providers as little as possible, while
steering the networked system to a desirable outcome. We also provide a
dimensionality-reduction procedure, which offers network-size independent
conditions. Finally, we illustrate our novel notions and algorithms on a
simulation setup stemming from digital market regulations for influencers, a
topic of growing interest
A Review of Active Management for Distribution Networks: Current Status and Future Development Trends
Driven by smart distribution technologies, by the widespread use of distributed generation sources, and by the injection of new loads, such as electric vehicles, distribution networks are evolving from passive to active. The integration of distributed generation, including renewable distributed generation changes the power flow of a distribution network from unidirectional to bi-directional. The adoption of electric vehicles makes the management of distribution networks even more challenging. As such, an active network management has to be fulfilled by taking advantage of the emerging techniques of control, monitoring, protection, and communication to assist distribution network operators in an optimal manner. This article presents a short review of recent advancements and identifies emerging technologies and future development trends to support active management of distribution networks
Foundations of Infrastructure CPS
Infrastructures have been around as long as urban
centers, supporting a society’s needs for its planning, operation,
and safety. As we move deeper into the 21st century, these
infrastructures are becoming smart – they monitor themselves,
communicate, and most importantly self-govern, which we denote
as Infrastructure CPS. Cyber-physical systems are now becoming
increasingly prevalent and possibly even mainstream. With the
basics of CPS in place, such as stability, robustness, and reliability
properties at a systems level, and hybrid, switched, and eventtriggered
properties at a network level, we believe that the time
is right to go to the next step, Infrastructure CPS, which forms
the focus of the proposed tutorial. We discuss three different
foundations, (i) Human Empowerment, (ii) Transactive Control,
and (iii) Resilience. This will be followed by two examples, one
on the nexus between power and communication infrastructure,
and the other between natural gas and electricity, both of which
have been investigated extensively of late, and are emerging to
be apt illustrations of Infrastructure CPS
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