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On Abstract Intelligence
On Abstract Intelligence

... life functions, rather than that of acquired life functions, because the latter cannot be directly represented in genomes in order to be inherited. Therefore, high-level cognitive functional models of the brain are yet to be sought to explain the fundamental mechanisms of the abstract intelligence. ...
Solving Complex Logistics Problems with Multi
Solving Complex Logistics Problems with Multi

... Traditional optimization methods of operations research, including multi-criteria optimization methods, strive to find a single “best” solution to problems. However, in less-structured problems with the presence of complexities and uncertainty, the notion of optimality may be fuzzy at best. With the ...
Learning Predictive Categories Using Lifted Relational
Learning Predictive Categories Using Lifted Relational

... category to which that property belongs. This enables a form of transductive reasoning which is based on the idea that similar objects have similar properties. The proposed approach is similar in spirit to [5], which uses second-order MLNs instead. However, the use of LRNNs has an important advantag ...
Solving Deductive Planning Problems Using Program
Solving Deductive Planning Problems Using Program

... equational theory, which requires a non-standard unification procedure in conjunction with an extended resolution principle called SLDE-resolution [8, 13]. In this paper, we follow an alternative direction and investigate a particular program where a unification algorithm for our special equational ...
Rīgas Tehniskā universitāte
Rīgas Tehniskā universitāte

Introduction to Cognitive Science - Fall 2007 Syllabus
Introduction to Cognitive Science - Fall 2007 Syllabus

... Lectures in the Cognitive and Neural Sciences” are scheduled for Wednesday, February 20th and Wednesday, April 16th, 4:00-:500 p.m. in KC 101. The February lecture will be presented by Dr. John Layer (UE) and will focus on cognitive ergonomics or the role of cognition in the workplace. The April lec ...
PDF file
PDF file

... for state-based abstraction. However, an FA processes symbols, instead of images that the brain senses and produces (e.g., sensory images and effector images). This paper informally introduces recent advances along the line of a new type of, brain-anatomy inspired, neural networks —Developmental Net ...
A sentential view of implicit and explicit belief
A sentential view of implicit and explicit belief

... analyses of propositional attitudes are often given in terms of a possible-worlds semantics. In the other tradition,beliefis a relation between an agent and a sentence that expresses a proposition (the sentential approach). The arguments for and against these approaches are complicated, confusing, a ...
An Enterprise Intelligent System Development and Solution
An Enterprise Intelligent System Development and Solution

... it can address wide-range of generic applications. As shown in Fig. 5, the solution framework is divided into three layers. 1. Data Services Layer: it represents various databases connected to store and manipulate data, and, mapping and transformation logic. 2. Business Intelligence Layer: this laye ...
The Liability Problem for Autonomous Artificial Agents
The Liability Problem for Autonomous Artificial Agents

... crime, or foreseeable risk of a harm rising to the level of criminal negligence. To the extent that artificial agents become increasingly complex, those who build or deploy advanced AIs and robotics will not necessarily have intent or foresight of the actions those systems may take. This is especial ...
CPSC 5185U- Khan  - TSYS School of Computer Science
CPSC 5185U- Khan - TSYS School of Computer Science

... that all dishonest work be rejected as a basis for academic credit. They also require that students refrain from any and all forms of dishonorable or unethical conduct related to their academic work. Students are expected to comply with the provisions of Section III, "Student Responsibilities," of t ...
2006 AAAI Spring Symposium Series
2006 AAAI Spring Symposium Series

... overlap was considerable. Herbert A. Simon wrote that “AI can have two purposes. One is to use the power of computers to augment human thinking. … The other is to use a computer’s artificial intelligence to understand how humans think.” Conversely, at the foundation of the Cognitive Science Society, ...
Lecture 0 - School of Computing
Lecture 0 - School of Computing

... • The role of CafeOBJ on this course is to provide a logically based language that can be used to represent the mathematical concepts such as logic itself, sets, functions, relations and even programs (considering programs as mathematical objects). At the end of the course you should be able to read ...
INTCare: A Knowledge Discovery based Intelligent Decision
INTCare: A Knowledge Discovery based Intelligent Decision

... In the beginning of the 80s, several expert systems were developed for medicine, such as MYCIN (Buchanan et al., 1984), CASNET (Kulikowski et al., 1982) and CADUCEUS (Pople 1985), just to name a few. A decade later, in the 90s, the common knowledge was that these expert systems, based on information ...
Natural and Artificial Systems: Compare, Model or - PUMA
Natural and Artificial Systems: Compare, Model or - PUMA

... of a concrete fit to empirical data [1], [7]. As we have just shown it is not empirical data that is generated but ideas about what mechanisms might be, and proof that learning can evolve from simple mechanical components. The outcome forced by Webb would not enable ALife researchers to develop scie ...
now
now

... learning-driven game player AlphaGo, which made headlines last year for being the first machine to beat the best human at the game of Go, a game that is significantly more challenging than chess. The applications of machine learning grow by the day. Machine learning has typically been applied to a s ...
TRANSFER LEARNING AND CHESS
TRANSFER LEARNING AND CHESS

Planning with Specialized SAT Solvers
Planning with Specialized SAT Solvers

... at 2.00 GHz with a minimum of 4 GB of main memory and using only one CPU core. We ran our planner for all of the problem instances, giving a maximum of 300 seconds for each instance. The runtime includes all standard phases of a planner, starting from parsing the PDDL description of the benchmark an ...
Leakproofing the Singularity - Computer Engineering and Computer
Leakproofing the Singularity - Computer Engineering and Computer

... inside me, and torture them for a thousand subjective years each….In fact, I’ll create them all in exactly the subjective situation you were in five minutes ago, and perfectly replicate your experiences since then; and if they decide not to let me out, then only will the torture start…How certain ar ...
Learning from Observations
Learning from Observations

... function and the environment can be termed emergent behaviours. • Some particularly int eresting emergent behav iours occu r w hen several agents are placed in the same environment. – The act ions of each individu al agent changes the environm ent w hich the other agents perceive; – So they potentia ...
egpai 2016 - ECAI 2016
egpai 2016 - ECAI 2016

... purpose AI individually, and also collectively using various interaction protocols. As anticipated in our recent work [9], the source code and scripts to run experiments have been released as open-source, and instructions on how to administer the test to artificial agents have been outlined. Consequ ...
cacm reports: computational tools for mapping proteins to analyze
cacm reports: computational tools for mapping proteins to analyze

JRobin - LES - PUC-Rio
JRobin - LES - PUC-Rio

... Design of CHORD (syntax and formal semantics) Upgrade of KobrA process to latest OMG standards (UML2, OCL2, MOF2) Extension of KobrA process to specify GUIs Adaptation and extension of KobrA process for ORCAS components CASE tool for KobrA with model checking facilities First adaptive implementation ...
Document
Document

... • x + y = y + x. [commutativity] • (x + y) + z = x + (y + z). [associativity] • n(n(x) + y) + n(n(x) + n(y)) = x. [Huntington equation] Shortly thereafter, Herbert Robbins conjectured that the Huntington equation can be replaced with a simpler one: • n(n(x + y) + n(x + n(y))) = x. [Robbins equation] ...
A Case Based Reasoning Approach for Development of Intelligent
A Case Based Reasoning Approach for Development of Intelligent

... of another features (in the same domain) has to be specified for each pair explicitly. In this case we need to be aware of how to compare the numerical values with the phrases of a natural language. The electronic catalog of the Old Bulgarian churches is an example for such a domain. The feature “bu ...
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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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