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Computing News – Spring 2016
Computing News – Spring 2016

... Cristian Cadar and Peter Pietzuch were the general chairs of the European Conference on Computer Systems, EuroSys 2016, hosted by Imperial College London between 18 and 21 April. EuroSys is one of the premier systems research conferences, which brings together professionals from both academia and i ...
CE213 Artificial Intelligence – Revision
CE213 Artificial Intelligence – Revision

...  To find best move using minimax search, given a game tree with heuristic values of leaf (terminal) nodes.  To identify rules that will fire and draw conclusions using forward chaining, given a set of rules and initial facts.  To determine the certainty of a conclusion using backward chaining and ...
Artificial Intelligence Methods - Lecture 1
Artificial Intelligence Methods - Lecture 1

...  The art of creating machines that perform functions that require intelligence when performed by people? ...
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18 LEARNING FROM OBSERVATIONS

... • If there are no examples left, it means that no such example has been observed, and we return a default value calculated from the majority classification at the node’s parent (or the majority classification at the root) • If there are no attributes left but still instances of several classes in th ...
Finished Paper - Villanova Computer Science
Finished Paper - Villanova Computer Science

the philosophy of artificial intelligence
the philosophy of artificial intelligence

... to examine to what extent the debate has moved forward since. For example, it was once argued that a computer would never be able to match humans in complicated reasoning tasks, including chess-playing at a world-class level. As is well known, computers have now surpassed that milestone. How much mo ...
Music Composition using Artificial Intelligence
Music Composition using Artificial Intelligence

... When they choose programming languages, computer scientists look for reliable languages that can create efficient programs as well as a better understanding about music [1]. The programming languages must have compatibility with the genetic algorithms to produce programs that can compose music. For ...
3. SOLVING PROBLEMS BY SEARCHING
3. SOLVING PROBLEMS BY SEARCHING

... OHJ-2556 Artificial Intelligence, Spring 2010 ...
- ePrints Soton - University of Southampton
- ePrints Soton - University of Southampton

Fuzzy Systems and Neuro-Computing in Credit Approval
Fuzzy Systems and Neuro-Computing in Credit Approval

... through all the rules. So Happy Together Fuzzy logic and neural networks are complementary technologies in the design of intelligent systems. Each method has its pros and cons. For example: • Artificial neural systems suffer from their inability to explain the steps by which they reach decisions and ...
Defining Artificial Intelligence
Defining Artificial Intelligence

... machines. The later definition stated: ‘Artificial intelligence is the study of ideas to bring into being machines that respond to stimulation consistent with traditional responses from humans, given the human capacity for contemplation, judgment and intention. Each such machine should engage in cri ...
“HUMaNITy SHOULD FEaR aDVaNCES IN aRTIFICIaL
“HUMaNITy SHOULD FEaR aDVaNCES IN aRTIFICIaL

... master player Lee Se-dol, at the notoriously difficult and abstract ancient Chinese board game GO [Ref: Guardian], in what was seen as another example of the march of artificial intelligence. It follows in the footsteps of IBM’s Deep Blue, which beat world chess champion Garry Kasparov in 1997 [Ref: ...
artificial intelligence applications especially the neural networks use
artificial intelligence applications especially the neural networks use

... Sometimes using GPS or other navigation doesn’t have to be the best solution. Driver has to decide about by-pass road or using highroad etc. There are models allowing designing such transport systems which consider safety and effectiveness of human mobility. Feed forward neural nets are used in anal ...
Expert Systems - Department of Computer Science
Expert Systems - Department of Computer Science

... Dreyfus: points out ways in which AI theorists have overclaimed about what they can do. e.g. Feigenbaum claims that ‘DENDRAL has been in use for many years at university and industrial chemical labs around the world’. But ‘..when we called several university and industrial sites that do mass spectro ...
Systems Intelligence - College of Engineering, Computing and
Systems Intelligence - College of Engineering, Computing and

... grounded on four basic principles: • Situatedness • Embodiment • Emergence ...
Haider - Computer Science - Illinois Institute of Technology
Haider - Computer Science - Illinois Institute of Technology

... McCarthy. He coined the term artificial intelligence which simply means making computers behave like humans. Computer behaving like humans is more than just thinking like humans. Also, it means that computer must behave and have emotions like humans. This is a challenging feat and his been a concept ...
Regulating Artificial Intelligence Systems
Regulating Artificial Intelligence Systems

... seem particularly unsuited to manage the risks associated with intelligent and autonomous machines. Ex ante regulation would be difficult because AI research and development may be discreet (requiring little physical infrastructure), discrete (different components of an AI system may be designed wit ...
Real-time decision problems: An operational research perspective
Real-time decision problems: An operational research perspective

... the real-time operation of a courier service company. This illustrative application will be used as a 'running' example throughout the paper. Let us consider a courier operator that receives calls for pick-up and delivery of priority mail. Each request consists of a location and a preferred or due d ...
Document
Document

... • The question to be resolved: “Is it possible to ask questions to identify which is which using only typewritten communications?” ...
Decision Support System
Decision Support System

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SARA A Software  Reuse Architecture  for  Building ... Systems
SARA A Software Reuse Architecture for Building ... Systems

... specific views. In a real world situation, the picture is somewhatmore complex. There will always be situations where modifications to some elements in the reuse frameworks are required for proper behavior. In an open environment like SARA, this can easily be done through classical object-oriented i ...
Brain-Like Artificial Intelligence: Analysis of a Promising Field
Brain-Like Artificial Intelligence: Analysis of a Promising Field

... which could lead to the same level of cognition, the same way there are plenty of different hardware which can support the exact same operating system in computer science. This approach, applied to Brain-Like Intelligence, is usually categorised as the Top-Down approach, being about the recreation ...
Fortnightly Thoughts
Fortnightly Thoughts

... of scale at an unprecedented pace. This has resulted in more connected devices and in turn, a lot more data being available for analysis. On the processing side, significant progress made in the field of neural networks and parallel computing in the last decade has meant that computers are now bette ...
The Application of Expert Systems in the Clinical Laboratory
The Application of Expert Systems in the Clinical Laboratory

... as a collection of conditional sentences referred to as “production rules.” A production rule consists of a set of preconditions, referred to as the premise, and an action part. lithe premise is true, the conclusion in the action part is justified. A prominent example of a system based on the produc ...
Use of Artificial Intelligence in Real Property Valuation
Use of Artificial Intelligence in Real Property Valuation

... sciences. Its use is more wide spread particularly in the fields of research and forecasting. When the objective is to construct a model directly from a set of measurements of the system's behavior, data-derived AI models are preferred which give qualitative outputs [9]. Application of various techn ...
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AI winter

In the history of artificial intelligence, an AI winter is a period of reduced funding and interest in artificial intelligence research. The term was coined by analogy to the idea of a nuclear winter. The field has experienced several hype cycles, followed by disappointment and criticism, followed by funding cuts, followed by renewed interest years or decades later. There were two major winters in 1974–80 and 1987–93 and several smaller episodes, including: 1966: the failure of machine translation, 1970: the abandonment of connectionism, 1971–75: DARPA's frustration with the Speech Understanding Research program at Carnegie Mellon University, 1973: the large decrease in AI research in the United Kingdom in response to the Lighthill report, 1973–74: DARPA's cutbacks to academic AI research in general, 1987: the collapse of the Lisp machine market, 1988: the cancellation of new spending on AI by the Strategic Computing Initiative, 1993: expert systems slowly reaching the bottom, and 1990s: the quiet disappearance of the fifth-generation computer project's original goals.The term first appeared in 1984 as the topic of a public debate at the annual meeting of AAAI (then called the ""American Association of Artificial Intelligence""). It is a chain reaction that begins with pessimism in the AI community, followed by pessimism in the press, followed by a severe cutback in funding, followed by the end of serious research. At the meeting, Roger Schank and Marvin Minsky—two leading AI researchers who had survived the ""winter"" of the 1970s—warned the business community that enthusiasm for AI had spiraled out of control in the '80s and that disappointment would certainly follow. Three years later, the billion-dollar AI industry began to collapse.Hypes are common in many emerging technologies, such as the railway mania or the dot-com bubble. An AI winter is primarily a collapse in the perception of AI by government bureaucrats and venture capitalists. Despite the rise and fall of AI's reputation, it has continued to develop new and successful technologies. AI researcher Rodney Brooks would complain in 2002 that ""there's this stupid myth out there that AI has failed, but AI is around you every second of the day."" In 2005, Ray Kurzweil agreed: ""Many observers still think that the AI winter was the end of the story and that nothing since has come of the AI field. Yet today many thousands of AI applications are deeply embedded in the infrastructure of every industry."" He added: ""the AI winter is long since over.""
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