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 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".

Engineering of Experience Based Trust for E-Commerce

2010 ◽  
pp. 342-367 ◽  
Author(s):  
Zhaohao Sun ◽  
Jun Han ◽  
Dong Dong ◽  
Shuliang Zhao
Keyword(s):  
Artificial Intelligence ◽  
Sustainable Development ◽  
Research And Development ◽  
Multiagent Systems ◽  
System Architecture ◽  
Intelligent Systems ◽  
Multiagent System ◽  
Theoretical Foundation ◽  
Knowledge Based ◽  
Trust Inference

Trust is significant for sustainable development of e-commerce and has received increasing attention in e-commerce, multiagent systems (MAS), and artificial intelligence (AI). However, little attention has been given to the theoretical foundation and intelligent techniques for trust in e-commerce from a viewpoint of intelligent systems and engineering. This chapter will fill this gap by examining engineering of experience-based trust in e-commerce from the viewpoint of intelligent systems. It looks at knowledgebased trust, inference-based trust and their interrelationships with experience-based trust. It also examines scalable trust in e-commerce. It proposes a knowledge based model of trust in e-commerce and a system architecture for METSE: a multiagent system for experience-based trust in e-commerce. The proposed approach in this chapter will facilitate research and development of trust, multiagent systems, e-commerce and e-services.

scholarly journals Advancing Post-Genome Data and System Integration through Machine Learning

2002 ◽  
Vol 3 (1) ◽  
pp. 28-31 ◽  
Author(s):  
Francisco Azuaje
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
System Integration ◽  
Intelligent Systems ◽  
Biological Data ◽  
Markup Languages ◽  
Public And Private ◽  
Genome Data ◽  
The Creation ◽  
Biological Data Integration

Research on biological data integration has traditionally focused on the development of systems for the maintenance and interconnection of databases. In the next few years, public and private biotechnology organisations will expand their actions to promote the creation of a post-genome semantic web. It has commonly been accepted that artificial intelligence and data mining techniques may support the interpretation of huge amounts of integrated data. But at the same time, these research disciplines are contributing to the creation of content markup languages and sophisticated programs able to exploit the constraints and preferences of user domains. This paper discusses a number of issues on intelligent systems for the integration of bioinformatic resources.

scholarly journals Behavioural Artificial Intelligence: An Agenda for Systematic Empirical Studies of Artificial Inference

2020 ◽  
Author(s):  
Tore Pedersen ◽  
Christian Johansen
Keyword(s):  
Artificial Intelligence ◽  
Media Coverage ◽  
Intelligent Systems ◽  
Human Life ◽  
Empirical Studies ◽  
Human Cognition ◽  
Artificial Intelligent ◽  
The Public ◽  
Computer Scientists ◽  
Intelligent Behavior

Artificial Intelligence (AI) receives attention in media as well as in academe and business. In media coverage and reporting, AI is predominantly described in contrasted terms, either as the ultimate solution to all human problems or the ultimate threat to all human existence. In academe, the focus of computer scientists is on developing systems that function, whereas philosophy scholars theorize about the implications of this functionality for human life. In the interface between technology and philosophy there is, however, one imperative aspect of AI yet to be articulated: How do intelligent systems make inferences? We use the overarching concept “Artificial Intelligent Behaviour” which would include both cognition/processing and judgment/behaviour. We argue that due to the complexity and opacity of Artificial Inference, one needs to initiate systematic empirical studies of artificial intelligent behavior similar to what has previously been done to study human cognition, judgment and decision making. This will provide valid knowledge, outside of what current computer science methods can offer, about the judgments and decisions made by intelligent systems. Moreover, outside academe – in the public as well as the private sector – expertise in epistemology, critical thinking and reasoning are crucial to ensure human oversight of the artificial intelligent judgments and decisions that are made, because only competent human insight into AI-inference processes will ensure accountability. Such insights require systematic studies of AI-behaviour founded on the natural sciences and philosophy, as well as the employment of methodologies from the cognitive and behavioral sciences.

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 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.

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.

Towards intelligent systems for boiler design

1997 ◽  
Vol 211 (5) ◽  
pp. 399-409 ◽  
Author(s):  
S Lu
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Fuzzy Logic ◽  
Intelligent Systems ◽  
State Of The Art ◽  
Knowledge Based Systems ◽  
Design Practice ◽  
Knowledge Based ◽  
Computer Aided ◽  
Boiler Design

This paper describes the application, through examples and comparisons, of artificial intelligence including neural networks, fuzzy logic, genetic algorithms in three levels of computer aided boiler design: design by mathematical modelling, design by optimization and design by knowledge-based systems. It reviews the state-of-the-art situation and trends for future development in boiler design practice.

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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