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Real-Time Credit-Card Fraud Detection using Artificial Neural
Real-Time Credit-Card Fraud Detection using Artificial Neural

... that it gets stuck in local minima and the error still remains the same. An evolutionary algorithm, Simulated Annealing and Genetic Algorithm, was given to solve this problem of local minima, among these algorithm simulated annealing is preferred because it takes less time in comparison with genetic ...
Anthropomorphism: Opportunities and Challenges
Anthropomorphism: Opportunities and Challenges

Chapter 10 Decision Support Systems
Chapter 10 Decision Support Systems

... What role do humans plan in automated decision-making applications?  What are some of the challenges faced by managers where automated decision-making systems are being used?  What solutions are needed to meet such challenges? ...
Description Logics and Planning - isi
Description Logics and Planning - isi

... moving action that does not require a transportation vehicle. If we describe moving actions in terms of their properties and constraints, they can be organized in a taxonomy and enable more efficient reasoning about actions through abstract classes. Simple action taxonomies that do not utilize descr ...
Preparation of Papers in Two-Column Format for
Preparation of Papers in Two-Column Format for

... Abstract-The emotions, set in simple words are what people feel. Emotional aspects have huge impact on Social intelligence like communication understanding, decision making and helps in understanding behavioral aspect of human. Human faces provide various information about emotions. As per psycholog ...
Forward and Backward Chaining and and
Forward and Backward Chaining and and

CS2053
CS2053

... 5. Davis E.Goldberg, “Genetic Algorithms: Search, Optimization and Machine Learning”, Addison Wesley, N.Y., 1989. 6. S. Rajasekaran and G.A.V.Pai, “Neural Networks, Fuzzy Logic and Genetic Algorithms”, PHI, 2003. 7. R.Eberhart, P.Simpson and R.Dobbins, “Computational Intelligence - PC Tools”, AP Pro ...
AAAI 2017 Conference Program
AAAI 2017 Conference Program

... 2017 Feigenbaum Prize The AAAI Feigenbaum Prize was established to recognize and encourage outstanding artificial intelligence research advances that are made by using experimental methods of computer science. The 2017 prize is being awarded to Yoav Shoham, Stanford University/Google, for highimpact ...
In 9122 Applied Soft Computing
In 9122 Applied Soft Computing

... games playing: programming computers to play games such as chess and checkers expert systems : programming computers to make decisions in real-life situations (for example, some expert systems help doctors diagnose diseases based on symptoms) natural language : programming computers to understand na ...
PDF
PDF

... tasks. Indeed forces play an important role in many skills that service robots should have, such as opening doors, pulling drawers, assembling things, and cutting slices of some foods, to name a few. We have proposed a learning framework7, where teacher demonstrations are encoded in a Hidden Markov ...
ICT619 Intelligent Systems
ICT619 Intelligent Systems

...  Similar to a goal-driven rule-based system, the inference engine in a frame-based system also searches for the goal.  But rules in such a system play an auxiliary role.  Frames represent here a major source of knowledge, and both methods and demons are used to add actions to the frames. ...
artificial intelligence - ABIT Group of Institutions
artificial intelligence - ABIT Group of Institutions

... world champion in a chess match when it bested Garry Kasparov by a score of 3.5 to 2.5 in an exhibition match (Goodman and Keene, 1997). Autonomous control: The ALVINN computer vision system was trained to steer a car to keep it following a lane. It was placed in CMU's NAVLAB computer-controlled min ...
The Model Checking Integrated Planning System (MIPS)
The Model Checking Integrated Planning System (MIPS)

... By conjoining this formula with any formula describing a set of states using variables A, B and C introduced before and querying the BDD engine for the possible instantiations of (A′ , B ′ , C ′ ), we can calculate all states that can be reached by driving the truck to San Francisco in some state fr ...
Form, function and the matter of experience
Form, function and the matter of experience

... alive, hence they do not have these properties’ to be far from convincing, specifically because the first premise is not well established but rather an issue of empirical investigation. Of course, it may turn out to be true that robots do not have feelings or purposes and beliefs, precisely because ...
6.034 Artificial Intelligence by T. Lozano
6.034 Artificial Intelligence by T. Lozano

... unlike FOL to describe fare restrictions. We will see later when we talk about natural language understanding that logic also plays a key role. There is another practical application of logic that is reasonably widespread namely logic programming. In this section, we will look briefly at logic progr ...
A Formal Characterization of Concept Learning in Description Logics
A Formal Characterization of Concept Learning in Description Logics

... discriminant power as required in tasks such as classification. In classification, observations to learn from are labeled as positive or negative instances of a given class. Characteristic induction is more suitable for finding regularities in a data set. This corresponds to learning from positive e ...
IOSR Journal of Computer Engineering (IOSR-JCE) e-ISSN: 2278-0661,p-ISSN: 2278-8727 PP 45-48 www.iosrjournals.org
IOSR Journal of Computer Engineering (IOSR-JCE) e-ISSN: 2278-0661,p-ISSN: 2278-8727 PP 45-48 www.iosrjournals.org

... some diet specifications and the précised treatment. Using Mamdani inference system, a combination of data mining technique with fuzzy rules was used in [9] to reduce count of attributes for cardiovascular disease diagnosis which covered two steps classification and diagnosis of the disease and rate ...
Expertise transfer and complex problems" using AQUINAS as a
Expertise transfer and complex problems" using AQUINAS as a

... appropriateness is easy to judge, and its result is unambiguous" (Szolovitz & Pauker, 1978). For example, in selecting a programming language, users may be able to say with certainty that they would be interested only in languages that run on an Apple Macintosh or that they will not consider a langu ...
A SURVEY OF THE APPLICATION OF MACHINE LEARNING IN
A SURVEY OF THE APPLICATION OF MACHINE LEARNING IN

... methods have to be selected with respect to the artifact and relevant evaluation metrics. Hevner et al. (2004) suggest to evaluate the artifact observational (in a case study or field study), analytical (by static analysis, architecture analysis, optimization, or dynamic analysis), experimental (in ...
CSE 5290: Artificial Intelligence
CSE 5290: Artificial Intelligence

... models that emulate some of the observed properties of biological nervous systems and draw on the analogies of adaptive biological learning. The key element of the ANN paradigm is the novel structure of the information processing system. It is composed of a large number of highly interconnected proc ...
Theorem provers an overview
Theorem provers an overview

... In natural deduction (NK) deductions are made from premisses by ‘introduction’ and ‘elimination’ rules. Some of the objections for LK can be applied to NK. 1) NK does not specify in which order the rules must be applied in the construction of a proof. 2) NK does not indicate which formula must be se ...
A Behavior Analytic Paradigm for Adaptive Autonomous Agents
A Behavior Analytic Paradigm for Adaptive Autonomous Agents

... repeatedly placed in the target situations, and the agent's behaviors are observed. The consequences are delivered to the agent (if the environment does not deliver them automatically). Complexity of the learned behaviors is limited, however, due to the sheer number of interactions with the environm ...
IEEE Transactions on Evolutionary Computation Special Issue on
IEEE Transactions on Evolutionary Computation Special Issue on

... vehicle routing problems) and bin packing (2D or strip packing, etc), space allocation, and so on. Variants of each of these problems, although classified under the same problem, often have widely differing constraints and problem features, thus requiring the design of efficient and adaptive algorit ...
s-cheran-g-gargano
s-cheran-g-gargano

... Believable Agents: It simulates emotions such that can pass as a human being Cooperative Problem Solving and Distributed AI: It could do almost anything like: system management, air-traffic control and CT image processing ...
Frontiers: Exploring the Digital Future of Management
Frontiers: Exploring the Digital Future of Management

... ’ve been thinking about technology and management for over report that their use of technology in their personal and home life a decade. In the process, I have written two books describing has far exceeded their experience of technology at work. Many insome of the ways that the practice of managemen ...
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History of artificial intelligence

The history of artificial intelligence (AI) began in antiquity, with myths, stories and rumors of artificial beings endowed with intelligence or consciousness by master craftsmen; as Pamela McCorduck writes, AI began with ""an ancient wish to forge the gods.""The seeds of modern AI were planted by classical philosophers who attempted to describe the process of human thinking as the mechanical manipulation of symbols. This work culminated in the invention of the programmable digital computer in the 1940s, a machine based on the abstract essence of mathematical reasoning. This device and the ideas behind it inspired a handful of scientists to begin seriously discussing the possibility of building an electronic brain.The field of AI research was founded at a conference on the campus of Dartmouth College in the summer of 1956. Those who attended would become the leaders of AI research for decades. Many of them predicted that a machine as intelligent as a human being would exist in no more than a generation and they were given millions of dollars to make this vision come true. Eventually it became obvious that they had grossly underestimated the difficulty of the project. In 1973, in response to the criticism of James Lighthill and ongoing pressure from congress, the U.S. and British Governments stopped funding undirected research into artificial intelligence. Seven years later, a visionary initiative by the Japanese Government inspired governments and industry to provide AI with billions of dollars, but by the late 80s the investors became disillusioned and withdrew funding again. This cycle of boom and bust, of ""AI winters"" and summers, continues to haunt the field. Undaunted, there are those who make extraordinary predictions even now.Progress in AI has continued, despite the rise and fall of its reputation in the eyes of government bureaucrats and venture capitalists. Problems that had begun to seem impossible in 1970 have been solved and the solutions are now used in successful commercial products. However, no machine has been built with a human level of intelligence, contrary to the optimistic predictions of the first generation of AI researchers. ""We can only see a short distance ahead,"" admitted Alan Turing, in a famous 1950 paper that catalyzed the modern search for machines that think. ""But,"" he added, ""we can see much that must be done.""
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