Toward Synthesizing Artificial Neural Networks that Exhibit Cooperative Intelligent Behavior: Some Open Issues in Artificial Life

1993 ◽  
Vol 1 (1_2) ◽  
pp. 111-134 ◽  
Author(s):  
Michael G. Dyer
Keyword(s):  
Animal Behavior ◽  
Artificial Life ◽  
Cooperative Behavior ◽  
Learning Processes ◽  
Open Problems ◽  
Developmental Learning ◽  
Biological Perspective ◽  
Intelligent Behavior ◽  
High Degree ◽  
Open Issues

The tasks that animals perform require a high degree of intelligence. Animals forage for food, migrate, navigate, court mates, rear offspring, defend against predators, construct nests, and so on. These tasks commonly require social interaction/cooperation and are accomplished by animal nervous systems, which are the result of billions of years of evolution and complex developmental/learning processes. The Artificial Life (AL) approach to synthesizing intelligent behavior is guided by this biological perspective. In this article we examine some of the numerous open problems in synthesizing intelligent animal behavior (especially cooperative behavior involving communication) that face the field of AL, a discipline still in its infancy.

Modeling Adaptive Autonomous Agents

1993 ◽  
Vol 1 (1_2) ◽  
pp. 135-162 ◽  
Author(s):  
Pattie Maes
Keyword(s):  
Animal Behavior ◽  
Artificial Life ◽  
Autonomous Agents ◽  
State Of The Art ◽  
Time Dependent ◽  
New Wave ◽  
Open Problems ◽  
New Approach ◽  
Unpredictable Environment ◽  
Main Ideas

One category of research in Artificial Life is concerned with modeling and building so-called adaptive autonomous agents, which are systems that inhabit a dynamic, unpredictable environment in which they try to satisfy a set of time-dependent goals or motivations. Agents are said to be adaptive if they improve their competence at dealing with these goals based on experience. Autonomous agents constitute a new approach to the study of Artificial Intelligence (AI), which is highly inspired by biology, in particular ethology, the study of animal behavior. Research in autonomous agents has brought about a new wave of excitement into the field of AI. This paper reflects on the state of the art of this new approach. It attempts to extract its main ideas, evaluates what contributions have been made so far, and identifies its current limitations and open problems.

scholarly journals MULTI-OBJECTIVE EVOLUTIONARY ALGORITHMS: FOUNDATION, DEVELOPMENT AND OPEN ISSUES

2018 ◽  
Vol 33 (3) ◽  
pp. 193-212
Author(s):  
Bùi Thu Lâm
Keyword(s):  
Reference Material ◽  
Evolutionary Algorithms ◽  
Evolutionary Computation ◽  
Special Class ◽  
Open Problems ◽  
Multi Objective ◽  
Computer Scientists ◽  
Open Issues

Evolutionary computation (EC) has been a fascinating branch of computation inspiredby a natural phenomenal of evolution. EC enables computer scientists to design eective algorithmsdealing dicult problems. This paper focuses on a special class problem called multi-objective optimizationproblems and evolutionary algorithms designed for it. We will overview the development ofmulti-objective evolutionary algorithms (MOEAs) over the years and problem diculties and thenindicate the open problems in this area. Our chief goal is to provide readers reference material in thearea of multi-objective evolutionary algorithms

Artificial Life as a Tool for Biological Inquiry

1993 ◽  
Vol 1 (1_2) ◽  
pp. 1-13 ◽  
Author(s):  
Charles Taylor ◽  
David Jefferson
Keyword(s):  
Cultural Evolution ◽  
Artificial Life ◽  
Living Systems ◽  
Grand Challenge ◽  
Open Problems ◽  
Maintenance Of Sex ◽  
Open Questions ◽  
Shifting Balance ◽  
The Origin Of Life ◽  
Natural Life

Artificial life embraces those human-made systems that possess some of the key properties of natural life. We are specifically interested in artificial systems that serve as models of living systems for the investigation of open questions in biology. First we review some of the artificial life models that have been constructed with biological problems in mind, and classify them by medium (hardware, software, or “wetware”) and by level of organization (molecular, cellular, organismal, or population). We then describe several “grand challenge” open problems in biology that seem especially good candidates to benefit from artificial life studies, including the origin of life and self-organi- zation, cultural evolution, origin and maintenance of sex, shifting balance in evolution, the relation between fitness and adaptedness, the structure of ecosystems, and the nature of mind.

Virtual Web Services

2011 ◽  
pp. 2460-2478
Author(s):  
Julio Fernández Vilas ◽  
Jose J. Pazos Arias ◽  
Ana Fernández Vilas
Keyword(s):  
Web Services ◽  
High Availability ◽  
Message Content ◽  
Business Logic ◽  
Web Servers ◽  
Dynamic Binding ◽  
Open Problems ◽  
Soap Message ◽  
Open Issues

Several open issues in Web services architecture are being solved by using different kinds of solutions. Standard high-availability techniques based on the use of Web servers, business-logic-based caching systems, dynamic binding of Web services by programming the access to a SOAP message content from the business logic layer, and other kinds of current open problems can now be handled using a common unique technique. What we propose is to apply virtualization techniques to Web services.

Virtual Web Services

2010 ◽  
pp. 74-94 ◽  
Author(s):  
Julio Fernández Vilas
Keyword(s):  
Web Services ◽  
High Availability ◽  
Message Content ◽  
Business Logic ◽  
Web Servers ◽  
Dynamic Binding ◽  
Open Problems ◽  
Soap Message ◽  
Open Issues

Several open issues in Web services architecture are being solved by using different kinds of solutions. Standard high-availability techniques based on the use of Web servers, business-logic-based caching systems, dynamic binding of Web services by programming the access to a SOAP message content from the business logic layer, and other kinds of current open problems can now be handled using a common unique technique. What we propose is to apply virtualization techniques to Web services.

scholarly journals Open problems of magnetic island control by electron cyclotron current drive

2016 ◽  
Vol 82 (6) ◽  
Author(s):  
D. Grasso ◽  
E. Lazzaro ◽  
D. Borgogno ◽  
L. Comisso
Keyword(s):  
Electron Cyclotron ◽  
Current Drive ◽  
Small Scale ◽  
Magnetic Islands ◽  
Magnetic Island ◽  
Open Problems ◽  
Scale Structures ◽  
Key Aspects ◽  
Small Scale Structures ◽  
Open Issues

This paper reviews key aspects of the problem of magnetic islands control by electron cyclotron current drive in fusion devices. On the basis of the ordering of the basic spatial and time scales of the magnetic reconnection physics, we present the established results, highlighting some of the open issues posed by the small-scale structures that typically accompany the nonlinear evolution of the magnetic islands and constrain the effect of the control action.

scholarly journals Wireless Sensor Networks Formation: Approaches and Techniques

2016 ◽  
Vol 2016 ◽  
pp. 1-18 ◽  
Author(s):  
Miriam Carlos-Mancilla ◽  
Ernesto López-Mellado ◽  
Mario Siller
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Research Area ◽  
Wireless Sensor ◽  
Open Problems ◽  
Key Factor ◽  
Network Backbone ◽  
Active Research ◽  
Selection Of ◽  
Open Issues

Nowadays, wireless sensor networks (WSNs) emerge as an active research area in which challenging topics involve energy consumption, routing algorithms, selection of sensors location according to a given premise, robustness, efficiency, and so forth. Despite the open problems in WSNs, there are already a high number of applications available. In all cases for the design of any application, one of the main objectives is to keep the WSN alive and functional as long as possible. A key factor in this is the way the network is formed. This survey presents most recent formation techniques and mechanisms for the WSNs. In this paper, the reviewed works are classified into distributed and centralized techniques. The analysis is focused on whether a single or multiple sinks are employed, nodes are static or mobile, the formation is event detection based or not, and network backbone is formed or not. We focus on recent works and present a discussion of their advantages and drawbacks. Finally, the paper overviews a series of open issues which drive further research in the area.

EDITORIAL

2002 ◽  
Vol 16 (07) ◽  
pp. 773-779 ◽  
Author(s):  
NIKHIL R. PAL ◽  
SRIMANTA PAL
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Real World ◽  
Computational Intelligence ◽  
Rough Sets ◽  
Artificial Life ◽  
Considerable Potential ◽  
Intelligence System ◽  
Intelligent Behavior ◽  
Real World Problems

Irrespective of the way computational intelligence (CI) is defined, its components should have the following characteristics: considerable potential in solving real world problems, ability to learn from experience, capability of self-organizing, and ability of adapting in response to dynamically changing conditions and constraints. To summarize, it should display aspects of intelligent behavior as observed in humans. In view of these, we assume that the major ingredients of a computational intelligence system are artificial neural networks, fuzzy sets, rough sets, and evolutionary computation. Some other components that may be parts of computational intelligence (CI) systems are artificial life and immuno computing. It is a synergistic combination of all these components.

Thirty Years of Computational Autopoiesis: A Review

2004 ◽  
Vol 10 (3) ◽  
pp. 277-295 ◽  
Author(s):  
Barry McMullin
Keyword(s):  
Research Program ◽  
Artificial Life ◽  
Living Systems ◽  
Basic Question ◽  
Santa Fe ◽  
Open Problems ◽  
Methodological Problems ◽  
Humberto Maturana ◽  
Distinctive Role

Computational autopoiesis—the realization of autopoietic entities in computational media—holds an important and distinctive role within the field of artificial life. Its earliest formulation by Francisco Varela, Humberto Maturana, and Ricardo Uribe was seminal in demonstrating the use of an artificial, computational medium to explore the most basic question of the abstract nature of living systems—over a decade in advance of the first Santa Fe Workshop on Artificial Life. The research program it originated has generated substantive demonstrations of progressively richer, lifelike phenomena. It has also sharply illuminated both conceptual and methodological problems in the field. This article provides an integrative overview of the sometimes disparate work in this area, and argues that computational autopoiesis continues to provide an effective framework for addressing key open problems in artificial life.

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