CORRELATION OF ARTIFICIAL INTELLIGENCE TECHNIQUES WITH SOFT COMPUTING IN VARIOUS AREAS

2017 ◽  
Vol 5 (4) ◽  
pp. 58-65
Author(s):  
Avinash Kumar ◽  
Abhishek Kumar ◽  
Arun Prasad Burnwal
Keyword(s):  
Artificial Intelligence ◽  
Information Processing ◽  
Soft Computing ◽  
Intelligent Agents ◽  
Intelligent Systems ◽  
Human Information Processing ◽  
Artificial Intelligence Techniques ◽  
Mathematical Techniques ◽  
Build System ◽  
Modern Era

Artificial Intelligence (AI) is a part of computer science concerned with designing intelligent computer systems that exhibit the characteristics used to associate with intelligence in human behavior. Basically, it define as a field that study and design of intelligent agents. Traditional AI approach deals with cognitive and biological models that imitate and describe human information processing skills. This processing skills help to perceive and interact with their environment. But in modern era developers can build system that assemble superior information processing needs of government and industry by choosing from large areas of mature technologies. Soft Computing (SC) is an added area of AI. It focused on the design of intelligent systems that process uncertain, imprecise and incomplete information. It applied in real world problems frequently to offer more robust, tractable and less costly solutions than those obtained by more conventional mathematical techniques. This paper reviews correlation of artificial intelligence techniques with soft computing in various areas.

scholarly journals Software Platform for Designing and Running Artificial Intelligence Competitions with a Visualization Subsystem

2019 ◽  
Author(s):  
Дмитрий Александрович Коростелев ◽  
Dmitriy Aleksandrovich Korostelev ◽  
Алексей Радченко ◽  
Aleksey Radchenko ◽  
Никита Сильченко ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Agents ◽  
Intelligent Systems ◽  
Software Platform ◽  
Main Approach ◽  
Specialized Software ◽  
Operational Testing ◽  
New Ideas ◽  
Systems Simulation

The paper describes the solution to the problem of testing the efficiency of new ideas and algorithms for intelligent systems. Simulation of interaction of the corresponding intelligent agents in a competitive form implementing different algorithms is proposed to use as the main approach to the solution. To support this simulation, a specialized software platform is used. The paper describes the platform developed for running competitions in artificial intelligence and its subsystems: a server, a client and visualization. Operational testing of the developed system is also described which helps to evaluate the efficiency of various algorithms of artificial intelligence in relation to the simulation like "Naval Battle".

Editorial: TRENDS IN AGGREGATION AND SECURITY ASSESSMENT FOR INFERENCE CONTROL IN STATISTICAL DATABASES

2002 ◽  
Vol 10 (05) ◽  
pp. 453-457 ◽  
Author(s):  
VICENÇ TORRA ◽  
JOSEP DOMINGO-FERRER
Keyword(s):  
Artificial Intelligence ◽  
Soft Computing ◽  
Data Handling ◽  
Security Assessment ◽  
Special Issue ◽  
Inference Control ◽  
Artificial Intelligence Techniques ◽  
Statistical Databases ◽  
Statistical Agencies ◽  
The Individual

As e-commerce and Internet-based data handling become pervasive, companies and statistical agencies have the need to exploit the data they accumulate without violating citizens' privacy. Inference control is a discipline whose goal is to prevent published/exchanged data from being linked with the individual respondents they originated from. This special issue illustrates that inference control largely draws on soft computing and artificial intelligence techniques.

scholarly journals A Survey of the Various Steganography Techniques Using Soft Computing Techniques

2021 ◽  
Vol 9 (VII) ◽  
pp. 1616-1619
Author(s):  
Er. Savita Devi
Keyword(s):  
Artificial Intelligence ◽  
Soft Computing ◽  
Secret Data ◽  
Artificial Intelligence Techniques ◽  
Individual Privacy ◽  
Soft Computing Techniques

Steganography is the method of storing information by hiding that information’s existence. It can be used to carry out hidden exchanges and hence can enhance individual privacy. Steganography aims at communicating the secret data in an appropriate multimedia carrier. In this paper, the various techniques used to perform Steganography in a secure way are studied and reviewed. In this the various Artificial Intelligence techniques used for steganography are reviewed and analyzed.

scholarly journals Beating Bomberman with Artificial Intelligence

2018 ◽  
Author(s):  
Juarez Monteiro ◽  
Roger Granada ◽  
Rafael C. Pinto ◽  
Rodrigo C. Barros
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Agents ◽  
Intelligent Agent ◽  
Digital Games ◽  
Complex Environments ◽  
Artificial Intelligence Techniques ◽  
Wide Range ◽  
Behavior Tree ◽  
Intelligent Behavior ◽  
Similar Complex

Artificial Intelligence (AI) seeks to bring intelligent behavior for machines by using specific techniques. These techniques can be employed in order to solve tasks, such as planning paths or controlling intelligent agents. Some tasks that use AI techniques are not trivially testable, since it can handle a high number of variables depending on their complexity. As digital games can provide a wide range of variables, they become an efficient and economical means for testing artificial intelligence techniques. In this paper, we propose a combination of a behavior tree and a Pathfinding algorithm to solve a maze-based problem using the digital game Bomberman of the Nintendo Entertainment System (NES) platform. We perform an analysis of the AI techniques in order to verify the feasibility of future experiments in similar complex environments. Our experiments show that our intelligent agent can be successfully implemented using the proposed approach.

scholarly journals An Integrative Framework for Artificial Intelligence Education

2019 ◽  
Vol 33 ◽  
pp. 9670-9677 ◽  
Author(s):  
Pat Langley
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Agents ◽  
System Integration ◽  
Intelligent Systems ◽  
Control Plan ◽  
Integrative Framework ◽  
Plan Generation ◽  
Knowledge Based ◽  
Intelligent Behavior ◽  
Intelligence Education

Modern introductory courses on AI do not train students to create intelligent systems or provide broad coverage of this complex field. In this paper, we identify problems with common approaches to teaching artificial intelligence and suggest alternative principles that courses should adopt instead. We illustrate these principles in a proposed course that teaches students not only about component methods, such as pattern matching and decision making, but also about their combination into higher-level abilities for reasoning, sequential control, plan generation, and integrated intelligent agents. We also present a curriculum that instantiates this organization, including sample programming exercises and a project that requires system integration. Participants also gain experience building knowledge-based agents that use their software to produce intelligent behavior.

scholarly journals Artificial Intelligence and Moral intelligence

1970 ◽  
Vol 4 (2) ◽  
pp. 254-264
Author(s):  
Laura Pana
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Agents ◽  
Intelligent Systems ◽  
Virtual Community ◽  
Machine Ethics ◽  
Moral Code ◽  
Human Beings ◽  
Artificial Intelligent ◽  
Moral Intelligence ◽  
Structural Levels

We discuss the thesis that the implementation of a moral code in the behaviour of artificial intelligent systems needs a specific form of human and artificial intelligence, not just an abstract intelligence. We present intelligence as a system with an internal structure and the structural levels of the moral system, as well as certain characteristics of artificial intelligent agents which can/must be treated as 1- individual entities (with a complex, specialized, autonomous or selfdetermined, even unpredictable conduct), 2- entities endowed with diverse or even multiple intelligence forms, like moral intelligence, 3- open and, even, free-conduct performing systems (with specific, flexible and heuristic mechanisms and procedures of decision), 4 – systems which are open to education, not just to instruction, 5- entities with “lifegraphy”, not just “stategraphy”, 6- equipped not just with automatisms but with beliefs (cognitive and affective complexes), 7- capable even of reflection (“moral life” is a form of spiritual, not just of conscious activity), 8 – elements/members of some real (corporal or virtual) community, 9 – cultural beings: free conduct gives cultural value to the action of a ”natural” or artificial being. Implementation of such characteristics does not necessarily suppose efforts to design, construct and educate machines like human beings. The human moral code is irremediably imperfect: it is a morality of preference, of accountability (not of responsibility) and a morality of non-liberty, which cannot be remedied by the invention of ethical systems, by the circulation of ideal values and by ethical (even computing) education. But such an imperfect morality needs perfect instruments for its implementation: applications of special logic fields; efficient psychological (theoretical and technical) attainments to endow the machine not just with intelligence, but with conscience and even spirit; comprehensive technical means for supplementing the objective decision with a subjective one. Machine ethics can/will be of the highest quality because it will be derived from the sciences, modelled by techniques and accomplished by technologies. If our theoretical hypothesis about a specific moral intelligence, necessary for the implementation of an artificial moral conduct, is correct, then some theoretical and technical issues appear, but the following working hypotheses are possible: structural, functional and behavioural. The future of human and/or artificial morality is to be anticipated.

scholarly journals 'Informees' as Informers? An Approach to Effective Informing

10.28945/2608 ◽  
2003 ◽  
Author(s):  
Iwona Miliszewska ◽  
Anne Venables
Keyword(s):  
Artificial Intelligence ◽  
Active Learning ◽  
Computer Science ◽  
Educational Research ◽  
Subject Matter ◽  
Intelligent Agents ◽  
Intelligent Systems ◽  
Science Degree ◽  
The Subject ◽  
Selection Of

An Intelligent Systems subject is offered in the final year of the Computer Science degree. The subject includes a diverse selection of topics in artificial intelligence and intelligent agents. The paper reflects on an innovative approach to the implementation of this subject. The development of the approach drew on educational research and the Informing Science paradigm. The aims of the approach included enga g-ing students in active learning, integrating theory with practice, and presenting the subject matter in an effective way. An innovative aspect of the approach was participatory teaching, i.e. students acting as guest lecturers and workshop presenters. The paper presents evaluation results indicating that the aims of the approach were achieved to a large extent.

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