scholarly journals Getting closer to the goal by being less capable

2019 ◽  
Vol 5 (2) ◽  
pp. eaau5902 ◽  
Author(s):  
Pedro D. Manrique ◽  
Mason Klein ◽  
Yao Sheng Li ◽  
Chen Xu ◽  
Pak Ming Hui ◽  
...  
Keyword(s):  
Autonomous Vehicles ◽  
Biological Evolution ◽  
Living Organism ◽  
Experimental Results ◽  
Bottom Up ◽  
Food Engineering

Understanding how systems with many semi-autonomous parts reach a desired target is a key question in biology (e.g., Drosophila larvae seeking food), engineering (e.g., driverless navigation), medicine (e.g., reliable movement for brain-damaged individuals), and socioeconomics (e.g., bottom-up goal-driven human organizations). Centralized systems perform better with better components. Here, we show, by contrast, that a decentralized entity is more efficient at reaching a target when its components are less capable. Our findings reproduce experimental results for a living organism, predict that autonomous vehicles may perform better with simpler components, offer a fresh explanation for why biological evolution jumped from decentralized to centralized design, suggest how efficient movement might be achieved despite damaged centralized function, and provide a formula predicting the optimum capability of a system’s components so that it comes as close as possible to its target or goal.

A UMDA-Based Discretization Method for Continuous Attributes

2011 ◽  
Vol 403-408 ◽  
pp. 1834-1838
Author(s):  
Jing Zhao ◽  
Chong Zhao Han ◽  
Bin Wei ◽  
De Qiang Han
Keyword(s):  
Machine Learning ◽  
Data Mining ◽  
Evolutionary Algorithms ◽  
Marginal Distribution ◽  
Convergence Speed ◽  
Fast Convergence ◽  
Experimental Results ◽  
Discretization Method ◽  
Bottom Up ◽  
Global Dynamic

Discretization of continuous attributes have played an important role in machine learning and data mining. They can not only improve the performance of the classifier, but also reduce the space of the storage. Univariate Marginal Distribution Algorithm is a modified Evolutionary Algorithms, which has some advantages over classical Evolutionary Algorithms such as the fast convergence speed and few parameters need to be tuned. In this paper, we proposed a bottom-up, global, dynamic, and supervised discretization method on the basis of Univariate Marginal Distribution Algorithm.The experimental results showed that the proposed method could effectively improve the accuracy of classifier.

scholarly journals The definition of life in the context of its origin

2006 ◽  
Vol 3 (1) ◽  
pp. 155-181 ◽  
Author(s):  
Y. N. Zhuravlev ◽  
V. A. Avetisov
Keyword(s):  
Genetic Information ◽  
Molecular Mechanisms ◽  
Biological Evolution ◽  
Living Organism ◽  
Living System ◽  
General Context ◽  
Control Mechanisms ◽  
Definition Of Life ◽  
Evolving System ◽  
Definition Of

Abstract. Current life is a complex multilevel phenomenon that is so diverse in its manifestations that a short and exhaustive definition of life is hardly possible. The high complexity of life, as well as a poor understanding of what life is in essence, are the obstacles to the elaboration of such a definition. Important characteristics of life, such as whole system-, ecosystem-, and information-defined characteristics have been included in the definition of life only recently. Ecosystem-defined characteristics have been absent in models of the pre-biotic state for a long time. However, without an ecosystem context, the concept of the emergence of life cannot be complete. Interconnections between living and non-living components of a primordial evolving system are decisive for the period of transition from chemical to biological evolution. Information-defined characteristics of life are often reduced to storage and the expression of genetic information, yet, the operation of such perfect processes in pre-biotic and transitional systems is unlikely. Genetic information, as defined in terms of the Shannon theory of communication, represents only a certain "informational channel" specified with respect to the expression of the structural genes. However, recent findings concerning the molecular mechanisms of the differential regulation of gene activity, and in the genomics, postgenomics and proteomics control mechanisms, suppose a richer diversity of informational flows in the organism. Moreover, considering life in more general context, other types of informational channels related, in particular, to the differentiation of higher taxa, hiatus, and expansion processes, should be kept in mind. In many publications devoted to the origin of life, the terms "living", "life", and "living organism" are freely interchanged that proves the vagueness of insights about the different levels of living system. This report considers some variants of the definition of life that have been recently suggested and are based on present-day knowledge of the structures and functions of life. The contradictory demands of a definition, that needs to be complete and short at the same time, are emphasized. A definition characterizing life as a state, a structure, and a process, is proposed.

scholarly journals Evolving the Controller of Automated Steering of a Car in Slippery Road Conditions

Algorithms ◽  
2018 ◽  
Vol 11 (7) ◽  
pp. 108 ◽  
Author(s):  
Natalia Alekseeva ◽  
Ivan Tanev ◽  
Katsunori Shimohara
Keyword(s):  
Genetic Programming ◽  
Autonomous Vehicles ◽  
Pid Controller ◽  
Control Model ◽  
Servo Control ◽  
Experimental Results ◽  
Pd Controller ◽  
Quality Of Control ◽  
Computing Paradigm

The most important characteristics of autonomous vehicles are their safety and their ability to adapt to various traffic situations and road conditions. In our research, we focused on the development of controllers for automated steering of a realistically simulated car in slippery road conditions. We comparatively investigated three implementations of such controllers: a proportional-derivative (PD) controller built in accordance with the canonical servo-control model of steering, a PID controller as an extension of the servo-control, and a controller designed heuristically via the most versatile evolutionary computing paradigm: genetic programming (GP). The experimental results suggest that the controller evolved via GP offers the best quality of control of the car in all of the tested slippery (rainy, snowy, and icy) road conditions.

scholarly journals MAKING OBJECT LEARNING AND RECOGNITION AN ACTIVE PROCESS

2008 ◽  
Vol 05 (02) ◽  
pp. 267-286 ◽  
Author(s):  
ALEŠ UDE ◽  
DAMIR OMRČEN ◽  
GORDON CHENG
Keyword(s):  
Object Recognition ◽  
Prior Knowledge ◽  
Experimental Results ◽  
3D Object Recognition ◽  
Object Representations ◽  
Active Process ◽  
Bottom Up ◽  
3D Object ◽  
3D Objects ◽  
Object Learning

The exploration and learning of new objects is an essential capability of a cognitive robot. In this paper we focus on making use of the robot's manipulation abilities to learn complete object representations suitable for 3D object recognition. Taking control of the object allows the robot to focus on relevant parts of the images, thus bypassing potential pitfalls of purely bottom-up attention and segmentation. The main contribution of the paper consists in integrated visuomotor processes that allow the robot to learn object representations by manipulation without having any prior knowledge about the objects. Our experimental results show that the acquired data is of sufficient quality to train a classifier that can recognize 3D objects independently of the viewpoint.

Improved Top-k Query Processing on Uncertain Data

2013 ◽  
Vol 380-384 ◽  
pp. 2837-2840
Author(s):  
Shuang Zhang ◽  
Shi Xiong Zhang
Keyword(s):  
Theoretical Analysis ◽  
Query Processing ◽  
Uncertain Data ◽  
Experimental Results ◽  
Bottom Up ◽  
Algorithm Efficiency ◽  
The Core ◽  
Query Algorithms

Bottom-up algorithm, which is one of the two probabilistic Top-k query algorithms, was improved. The core of the bottomup algorithm is the iteration on the three courses of bounding, pruning,and refining towards the objects and instances. The main contribution is to change the iteration on instances of objects one by one into iterating all the instances of objects from the superior to the inferior;and to transform the condition and sequence of pruning in order to make the pruning more effective. Theoretical analysis and experimental results show that the algorithm efficiency could be obviously increased by about 20%.

scholarly journals Hierarchy Restructuring for Hierarchical LVS Comparison

VLSI Design ◽  
1999 ◽  
Vol 10 (1) ◽  
pp. 117-125 ◽  
Author(s):  
Wonjong Kim ◽  
Hyunchul Shin
Keyword(s):  
Pattern Matching ◽  
Experimental Results ◽  
Memory Usage ◽  
Comparison System ◽  
Bottom Up ◽  
Rule Based ◽  
Matching Algorithm ◽  
Cpu Time ◽  
Layout Verification ◽  
Comparison Technique

A new hierarchical layout vs. schematic (LVS) comparison system for layout verification has been developed. The schematic hierarchy is restructured to remove ambiguities for consistent hierarchical matching. Then the circuit hierarchy is reconstructed from the layout netlist by using a modified SubGemini algorithm recursively in bottom-up fashion. For efficiency, simple gates are found by using a fast rule-based pattern matching algorithm during preprocessing. Experimental results show that our hierarchical netlist comparison technique is effective and efficient in CPU time and in memory usage, especially when the circuit is large and hierarchically structured.

scholarly journals Self-Organization of the Biological Evolution

Genes ◽  
2019 ◽  
Vol 10 (11) ◽  
pp. 854
Author(s):  
Arber
Keyword(s):  
Genetic Variants ◽  
Molecular Genetic ◽  
Bacterial Genome ◽  
Genetic Research ◽  
Biological Evolution ◽  
Living Organism ◽  
Bacterial Strains ◽  
Different Types ◽  
Set Up ◽  
The One

We report here experiments carried out with nonpathogenic Escherichia coli bacterial strains and their phages. This research yielded interesting insights into their activities, occasionally producing genetic variants of different types. In order to not interfere with the genetic stability of the parental strains involved, we found that the bacteria are genetically equipped to only rarely produce a genetic variant, which may occur by a number of different approaches. On the one hand, the genes of relevance for the production of specific genetic variants are relatively rarely expressed. On the other hand, other gene products act as moderators of the frequencies that produce genetic variants. We call the genes producing genetic variants and those moderating the frequencies of genetic variation “evolution genes”. Their products are generally not required for daily bacterial life. We can, therefore, conclude that the bacterial genome has a duality. Some of the bacterial enzymes involved in biological evolution have become useful tools (e.g., restriction endonucleases) for molecular genetic research involving the genetic set-up of any living organism.

scholarly journals Taxonomy of bio-inspired optimization algorithms

2019 ◽  
Vol 8 (2) ◽  
pp. 23 ◽  
Author(s):  
Saman M. Almufti ◽  
Ridwan Boya Marqas ◽  
Vaman Ashqi Saeed
Keyword(s):  
Computer Science ◽  
Optimization Problems ◽  
Optimization Algorithms ◽  
Biological Evolution ◽  
Living Organism ◽  
Complex Optimization ◽  
Biological Field

Bio-Inspired optimization algorithms are inspired from principles of natural biological evolution and distributed collective of a living organism such as (insects, animal, …. etc.) for obtaining the optimal possible solutions for hard and complex optimization problems. In computer science Bio-Inspired optimization algorithms have been broadly used because of their exhibits extremely diverse, robust, dynamic, complex and fascinating phenomenon as compared to other existing classical techniques.This paper presents an overview study on the taxonomy of bio-inspired optimization algorithms according to the biological field that are inspired from and the areas where these algorithms have been successfully applied

Sign in / Sign up

Export Citation Format

Share Document