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Qualitative Spatial Reasoning: Framework and Frontiers
Qualitative Spatial Reasoning: Framework and Frontiers

... Diagrams and models seem inextricably linked with human spatial reasoning. Why? The wealth of concrete detail in such analog spatial representations at first might seem more than necessary for most spatial questions. Perhaps there are more abstract representations of shape and space which by themsel ...
Survey on Fuzzy Expert System
Survey on Fuzzy Expert System

... by knowledge engineers, which has the ability to replicate the thinking and reasoning capacity of human being based on some facts and rules present on it. Expert Systems provide an expert view of a problem in a specific domain area by accepting the input from user. But, the input gathered from human ...
Employing a Java Expert System Shell for Intelligent - CEUR
Employing a Java Expert System Shell for Intelligent - CEUR

... In such a situation time is inevitably expended in the communication of requirements, specifications and constraints. Thus, given the increasing demand for full commercial-scale ITS and the large development time for such systems, there is clearly a need for the ITS development process to be made fa ...
A First Study of Fuzzy Cognitive Maps Learning Using Particle
A First Study of Fuzzy Cognitive Maps Learning Using Particle

... preliminary results on a different approach, based on Evolution Strategies, have been reported [23]. This paper proposes, a new approach for FCM learning, which is based on the Particle Swarm Optimization (PSO) method. PSO is used for the determination of proper weight matrices for the system, throu ...
now
now

... Business analytics implies the use of models and data to improve an organization's performance and/or competitive posture Web analytics implies using business analytics on real-time Web information to assist in decision making; often related to eCommerce Predictive analytics describes the business a ...
Negation Without Negation in Probabilistic Logic Programming
Negation Without Negation in Probabilistic Logic Programming

... Representing CPDs Without Negations Negative noise probabilities in acyclic programs allow us to express CPDs that cannot otherwise be expressed without negations. For example, the last two lines in Example 3 represent a non-monotonic CPD P(B | A). Theorem 1. Consider a set R of negation-free probab ...
call for papers - IUI 2017
call for papers - IUI 2017

... or the other, we address the complex interaction between the two. We welcome research that explores how to make the interaction between computers and people smarter, which may leverage solutions from data mining, knowledge representation, novel interaction paradigms, and emerging technologies. We st ...
CTL AgentSpeak(L): a specification language for agent programs
CTL AgentSpeak(L): a specification language for agent programs

... if φ is a logical consequence of the beliefs bs of ag. An agent is said to intend the atomic formula φ, if φ is the subject of an achieve goal in the active intentions of the agent (CI ) or in his suspended intentions associated to events to be processed (CE ). An agent is said to desire the atomic ...
25. Dopamine and Planning - USC
25. Dopamine and Planning - USC

... 6). The act left was elicited (bottom line) when the integrated signal reached a threshold. (B) A trial at the end of the exploration phase. When stimulus blue was presented (line 1), the model elicited the act right (bottom line) that led to presentation of stimulus green (line 1). Since stimulus g ...
The Hidden Pattern
The Hidden Pattern

... forward a fair bit, and hopefully created some tools that will accelerate future progress. Patternist philosophy isn’t something with a fixed number of axioms and conclusions. It’s a fluid and shifting set of interlocking ideas – most of all, it’s a way of thinking about the mind. Transmitting a dee ...
Reasoning about Time
Reasoning about Time

... totally ordered) or branching (for example, each branch may represent a possible future evolution of the given world). Circular time is also used in some applications. (See Van Benthem (1983) for a detailed analysis of these alternatives.) Naturally, different approaches have been proposed and diffe ...
PPT - Sheffield Department of Computer Science
PPT - Sheffield Department of Computer Science

... sentences. Provides an account of productivity and systematicity. Human language is productive, (no limit to number of sentences we can produce). And systematic (if you can say John loves Mary, you can also say Mary loves John) Human thought: productive and systematic because it relies on Mentalese, ...
Creativity, Cognitive Mechanisms, and Logic
Creativity, Cognitive Mechanisms, and Logic

... During the last decades many cognitive abilities of humans have been modeled with computational approaches trying to formally describe such abilities, to develop algorithmic solutions for concrete implementations, and to build robust systems that are of practical use in application domains. Whereas ...
AI Techniques for Personalized Recommendation Tutorial
AI Techniques for Personalized Recommendation Tutorial

... recommendation. The algorithms, applications, and interfaces presented will be illustrated through a set of case studies drawn from both research and commercial systems. The target audience comprises (a) attendees from industry who seek an authoritative update on recommendation technology; (b) AI re ...
Survey on Remotely Sensed Image Classification
Survey on Remotely Sensed Image Classification

... quality mapping through a chosen metric distance function. Thus the segmentation problem becomes solvable by a regular categorization algorithm. Sparse SVM is adopted to radically decrease the regions that are needed to classify images. The chosen regions by a sparse SVM estimated to the target conc ...
Swarm Intelligence Optimization Algorithms and Their Application
Swarm Intelligence Optimization Algorithms and Their Application

... Swarm intelligence optimization algorithm has passed continuous development and maturity in decades. It has been successfully applied in many fields with its simple, efficient and many other advantages, so it has achieved many good results. The study shows that swarm intelligence optimization algori ...
Knowledge-based agents
Knowledge-based agents

... Perceived as a major break-through in the late 50ies, just after the birth of artificial intelligence as a discipline (maybe the same brake-through still has to be realized in game-AI..) Model not only knowledge, but also lack thereof (uncertainty) Logic based approach 1: epistemic logic Logic based ...
Artificial Intelligence and Expert Systems
Artificial Intelligence and Expert Systems

... Testing for Intelligence An interesting test designed to determine whether a computer exhibits intelligent behavior was designed by Alan Turing and is called the Turing test. A computer can be considered to be smart only when a human interviewer, “conversing” with both an unseen human being and an u ...
The use of theorem-proving techniques in question
The use of theorem-proving techniques in question

... base general facts about the relations of the logical system, e.g., the fact that set inclusion is transitive, as well as specific facts about the objects in the real domain, e.g., the fact that John is a member of the set of all boys. If such general information were present in the data, the logica ...
ppt - CSE, IIT Bombay
ppt - CSE, IIT Bombay

... the artificial-intelligence community'. The different models of conceptbased perception are suggested as attempts at solving this problem. A machine with a developed concept-based perception can be rightly taken as a 'thinking machine'. The second problem is-'experience barrier' as I would call it-o ...
Topic_2B_Expert_Systems
Topic_2B_Expert_Systems

...  The WHEN NEEDED method attached to the attribute Evaluation is used to establish its value.  The inference engine executes this method when it needs to determine the value of Evaluation.  If based on the set of rules provided for credit evaluation, the inference engine cannot establish the value ...
A Comparative Utility Analysis of Case
A Comparative Utility Analysis of Case

... that the CA uses to perform its computations. The hardware architecture HA defines the types of operations that a system can perform at the implementation level, as well as the relative costs of such operations. The cost (and hence the utility) of an operation may be different on different HA’s: for ...
Independence in Relational Languages with Finite Domains
Independence in Relational Languages with Finite Domains

... Getoor et al. 2001, Poole 2003, de Salvo Braz et al. 2006]. The second group of languages is more restricted than the first in the kinds of logical sentences and probabilistic assessments that are allowed. Often the languages in the second group are based on graphical models such as Bayesian network ...
Real Time Fault Detection and Isolation: A Comparative Study
Real Time Fault Detection and Isolation: A Comparative Study

... are applied and method compare criterion most have been based on qualitative metric. However, to confirm more excellent method, quantitative criterion comparison is considered. There are different methods in dealing with faults: State-based approach: In this method, diagnosis by verified system stat ...
Artificial Intelligence
Artificial Intelligence

... If a student cannot attend lectures/tutorials it is the student’s responsibility to find out what was discussed in lectures / tutorials (possible changes to assignments, questions & answers). ...
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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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