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Consulta: repository:"192" Registros recuperados: 900 Máximo de
Consulta: repository:"192" Registros recuperados: 900 Máximo de

... To contribute on the evaluative process of searching the appropriate designing paradigms as a mechanical engineer, I bring up in this paper some of my ideas about the robot hand design concretely. While the designs of my robot hands may seem to be filled with eccentric, vagarious and serendipitous i ...
Towards a Self-Manufacturing Rapid Prototyping Machine Volume 1
Towards a Self-Manufacturing Rapid Prototyping Machine Volume 1

... 9.3.7 Optimising Darwin’s design to reduce the requirements for self-manufacture......................................................................... 167 Implications of the RepRap printer on society........................................... 172 The RepRap printer as a low risk analogy for a se ...
Multiagent Systems : A Modern Approach to Distributed Artificial
Multiagent Systems : A Modern Approach to Distributed Artificial

... • Theory. It gives a clear and careful presentation of the key concepts, methods, and algorithms that form the core of the field. Many illustrations and examples are provided. • Practice. The emphasis is not only on theory, but also on practice. In particular, the book includes a number of thoughtpr ...
The Quest for Artificial Intelligence - Stanford Artificial Intelligence
The Quest for Artificial Intelligence - Stanford Artificial Intelligence

... 10.1 At MIT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 189 10.2 At Stanford . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 190 10.3 In Japan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 193 10.4 Edinburgh’s “FREDDY” . . . . . . . . . . . . . . . . ...
DOMAIN-INDEPENDENT LOCAL SEARCH for LINEAR INTEGER
DOMAIN-INDEPENDENT LOCAL SEARCH for LINEAR INTEGER

... can outperform or compete with state-of-the-art integer programming (IP) branchand-bound and constraint programming (CP) approaches to these problems in finding near-optimal solutions. Key findings of our empirical study include that integer local search is able to solve difficult constraint problem ...
Analysis of the Dynamics of Reasoning Using Multiple
Analysis of the Dynamics of Reasoning Using Multiple

... (Johnson-Laird, 1983; Yang and Johnson-Laird, 1999). Reasoning steps in natural contexts are usually not restricted to the application of logical inference rules. For example, a step in a reasoning process may involve translation of information from one representation form (e.g., geometrical) into a ...
Goal Dependency Set Primer - EECS @ Michigan
Goal Dependency Set Primer - EECS @ Michigan

... - Want to be able to remember these things independent of any justification ...
Limitations of Front-To-End Bidirectional Heuristic Search
Limitations of Front-To-End Bidirectional Heuristic Search

... If a unidirectional heuristic search expands the majority of its nodes deeper than the solution midpoint, we call its heuristic weak and show that a bidirectional heuristic search expands no fewer nodes than a bidirectional bruteforce search. If the majority are expanded at shallower depth than the ...
Limitations of Front-to-End Bidirectional Heuristic Search
Limitations of Front-to-End Bidirectional Heuristic Search

... If a unidirectional heuristic search expands the majority of its nodes deeper than the solution midpoint, we call its heuristic weak and show that a bidirectional heuristic search expands no fewer nodes than a bidirectional bruteforce search. If the majority are expanded at shallower depth than the ...
Neural Networks
Neural Networks

... altered them to suit this text. Last but not least I want to thank two people who made outstanding contributions to this work who occupy, so to speak, a place of honor: My girlfriend Verena Thomas, who found many mathematical and logical errors in my text and discussed them with me, although she has ...
Neural Networks
Neural Networks

... altered them to suit this text. Last but not least I want to thank two people who made outstanding contributions to this work who occupy, so to speak, a place of honor: My girlfriend Verena Thomas, who found many mathematical and logical errors in my text and discussed them with me, although she has ...
E - Read
E - Read

... “The performance of randomized algorithms depends on the distribution of the input.” Clarification: Not at all (for this course) – For example, our analysis for RandQS did not assume that n! possible permutations for the input are given to RandQS with probability 1/(n!). More precisely, the expected ...
The Traveling Salesman Problem
The Traveling Salesman Problem

... The no subtour constraint can also be formulated in two ways ◮ The number of links in any subset should be less than the number of cities in the subset. X ...
Varieties of Analogical Reasoning
Varieties of Analogical Reasoning

... As a strategy in decision making and sensemaking, as well as a rhetorical device, the analogy concept expanded greatly over the centuries since Aristotle discussed proportional analogies. In his System of Logic (1982, Ch.20), John Stuart Mill echoed Etienne de Condillac's definition of analogy, "the ...
Overview of Computer Science - CSE User Home Pages
Overview of Computer Science - CSE User Home Pages

... at the University of Minnesota-Twin Cities. More information about that class and these notes are in the opening chapter. The original version of these notes was used in the Spring 2014 offering of that class. This current version, Version 1.2, is a small update, containing some minor clarifications ...
OPERATIONS MANAGEMENT II
OPERATIONS MANAGEMENT II

... sequencing does not refer to time. For example, if a bank teller processes 5 customers, the bank teller may just process the customers on a first come first served basis without any planning about exact start and end times for each customer. That’s sequencing. Scheduling, in contrast, produces a det ...
A Knowledge-Based Approach to Lexical Analogy
A Knowledge-Based Approach to Lexical Analogy

... This transformation is valuable because the noun taxonomy is the most richly developed in WordNet, and the subsumption relations it contains will form a key part of the analogical similarity measure. 2. Each pairing of terms in the analogy undergoes a simple path analysis, to determine whether each ...
Research Article Classification of Textual E-Mail Spam
Research Article Classification of Textual E-Mail Spam

... ant colony algorithm, and neural network algorithm GEM (Gaussian expectation-maximization), are usually used [21– 26]. The up-to-date survey of evolutionary algorithms for clustering, especially the partition algorithms, are described in detail in [27]. The comparison of advanced topics like multiob ...
Triangle Theorems - School of Computer Science, University of
Triangle Theorems - School of Computer Science, University of

... perceive, understand, reason about, construct, and make use of, structures and processes in the environment -- competences that are also present in pre-verbal humans, e.g. toddlers. Human toddlers, and some other animals, seem to be able to make such discoveries, but they lack the meta-cognitive com ...
Searching for Arthur Koestler`s Holons – a systemstheoretical
Searching for Arthur Koestler`s Holons – a systemstheoretical

... networks by the concept of a multi-strata hierarchy of some depth is therefore not feasible. For artificial neural networks the trivial multi-strata decomposition consisting of a black-box to describe the behavior on the most upper level and the network of artificial neurons on the next lower level, ...
On real-world temporal pattern recognition using Liquid State
On real-world temporal pattern recognition using Liquid State

... and so do systems that mimic nature like artificial neural networks. However, there are serious problems with these computational techniques when it comes to training and controlling their dynamics when dealing with input over time. ...
Representation of Behavioral Knowledge for Planning and Plan
Representation of Behavioral Knowledge for Planning and Plan

... situation and/or end situation. Each path from a start situation to an end situation defines a sequence of situations represented by the situation graph. To refine a single situation scheme, it has to be connected to one or more situation graphs by so called specialization edges. Imagine for example ...
The Quest for Artificial Intelligence
The Quest for Artificial Intelligence

... This draft is almost complete and is close to what I will be sending to the publisher, Cambridge University Press, in February 2009. Some things still need to be added, such as dates associated with people. (The stand-ins for some of these are now written as “19[[xx]]– ”.) Also, I need to get permis ...
LIFE ON A DESERT ISLAND - UMD Department of Computer Science
LIFE ON A DESERT ISLAND - UMD Department of Computer Science

... global properties of the reasoning system (i.e., its set of axioms). Time is then taken to assess logical consequences of these properties before a commonsense conclusion is drawn. Thus a strong flavor of idealized reasoning has persisted. Suppose we would like to have a reasoning system use a rule ...
optical multistage interconnection networks
optical multistage interconnection networks

... (neurons) working in unison to solve specific problems. ANNs, like people, learn by example. An ANN is configured for a specific application, such as pattern recognition or data classification through a learning process. Learning in biological systems involves adjustments to the synaptic connections ...
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Artificial intelligence

Artificial intelligence (AI) is the intelligence exhibited by machines or software. It is also the name of the academic field of study which studies how to create computers and computer software that are capable of intelligent behavior. Major AI researchers and textbooks define this field as ""the study and design of intelligent agents"", in which an intelligent agent is a system that perceives its environment and takes actions that maximize its chances of success. John McCarthy, who coined the term in 1955, defines it as ""the science and engineering of making intelligent machines"".AI research is highly technical and specialized, and is deeply divided into subfields that often fail to communicate with each other. Some of the division is due to social and cultural factors: subfields have grown up around particular institutions and the work of individual researchers. AI research is also divided by several technical issues. Some subfields focus on the solution of specific problems. Others focus on one of several possible approaches or on the use of a particular tool or towards the accomplishment of particular applications.The central problems (or goals) of AI research include reasoning, knowledge, planning, learning, natural language processing (communication), perception and the ability to move and manipulate objects. General intelligence is still among the field's long-term goals. Currently popular approaches include statistical methods, computational intelligence and traditional symbolic AI. There are a large number of tools used in AI, including versions of search and mathematical optimization, logic, methods based on probability and economics, and many others. The AI field is interdisciplinary, in which a number of sciences and professions converge, including computer science, mathematics, psychology, linguistics, philosophy and neuroscience, as well as other specialized fields such as artificial psychology.The field was founded on the claim that a central property of humans, human intelligence—the sapience of Homo sapiens—""can be so precisely described that a machine can be made to simulate it."" This raises philosophical issues about the nature of the mind and the ethics of creating artificial beings endowed with human-like intelligence, issues which have been addressed by myth, fiction and philosophy since antiquity. Artificial intelligence has been the subject of tremendous optimism but has also suffered stunning setbacks. Today it has become an essential part of the technology industry, providing the heavy lifting for many of the most challenging problems in computer science.
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