- University of Huddersfield Repository
... domain models. Shah et al. (2013) explored the deployment of automated planning to assist in the development of domain models for different real-world applications. Currently, there is no published comparison research on KE tools for AI planning that automatically encode a domain model from observin ...
... domain models. Shah et al. (2013) explored the deployment of automated planning to assist in the development of domain models for different real-world applications. Currently, there is no published comparison research on KE tools for AI planning that automatically encode a domain model from observin ...
Tarek R. Besold, Kai
... of AI working on computational models for creativity, concept formation, concept discovery, idea generation, and their overall relation and role to general intelligence as well as researchers focusing on application areas, like computer-aided innovation. Although the different approaches to question ...
... of AI working on computational models for creativity, concept formation, concept discovery, idea generation, and their overall relation and role to general intelligence as well as researchers focusing on application areas, like computer-aided innovation. Although the different approaches to question ...
pdf
... areas of interest for AI began to crystallize. These areas targeted individual intelligent capabilities: knowledge representation, planning, computer vision, natural language understanding, machine learning, etc. In what later became known as classical AI, these problems were generally tackled by id ...
... areas of interest for AI began to crystallize. These areas targeted individual intelligent capabilities: knowledge representation, planning, computer vision, natural language understanding, machine learning, etc. In what later became known as classical AI, these problems were generally tackled by id ...
Paper Title (use style: paper title)
... of data may be classified as hybrid DSS providing modeling, data retrieval, and data summarization functionality. ModelDriven DSS use data and parameters provided by decision-makers to aid them in analyzing a situation, but they are not usually data intensive. Very large databases are usually not ne ...
... of data may be classified as hybrid DSS providing modeling, data retrieval, and data summarization functionality. ModelDriven DSS use data and parameters provided by decision-makers to aid them in analyzing a situation, but they are not usually data intensive. Very large databases are usually not ne ...
Registration Brochure - Association for the Advancement of Artificial
... In nearly every subfield of artificial intelligence, it is both true and well known that using the right representation is crucial. For example, in some problem domains, moving from state-space planning to plan-space planning can make previously intractable problems solvable. The problem of finding ...
... In nearly every subfield of artificial intelligence, it is both true and well known that using the right representation is crucial. For example, in some problem domains, moving from state-space planning to plan-space planning can make previously intractable problems solvable. The problem of finding ...
decision support
... Government regulations and the need for compliance, political instability and terrorism, competition, and changing consumer demands produce more uncertainty, making it more difficult to predict consequences and the future Other factors are the need to make rapid decisions, the frequent and unpredict ...
... Government regulations and the need for compliance, political instability and terrorism, competition, and changing consumer demands produce more uncertainty, making it more difficult to predict consequences and the future Other factors are the need to make rapid decisions, the frequent and unpredict ...
now
... Government regulations and the need for compliance, political instability and terrorism, competition, and changing consumer demands produce more uncertainty, making it more difficult to predict consequences and the future Other factors are the need to make rapid decisions, the frequent and unpredict ...
... Government regulations and the need for compliance, political instability and terrorism, competition, and changing consumer demands produce more uncertainty, making it more difficult to predict consequences and the future Other factors are the need to make rapid decisions, the frequent and unpredict ...
Machine Learning CSCI 5622
... • No hands across America (driving autonomously 98% of the time from Pittsburgh to San Diego) • During the 1991 Gulf War, US forces deployed an AI logistics planning and scheduling program that involved up to 50,000 vehicles, cargo, and people • NASA's on-board autonomous planning program controlled ...
... • No hands across America (driving autonomously 98% of the time from Pittsburgh to San Diego) • During the 1991 Gulf War, US forces deployed an AI logistics planning and scheduling program that involved up to 50,000 vehicles, cargo, and people • NASA's on-board autonomous planning program controlled ...
1986 - Plausibility of Diagnostic Hypotheses: The Nature of Simplicity
... multiple disorders can AI systems have traditionally hanoccur simultaneously. dled the potential combinatorial explosion of possible hypotheses in such problems by focusing attention on a This raises the issue of estabfew “most plausible” ones. lishing what makes one hypothesis more plausible than o ...
... multiple disorders can AI systems have traditionally hanoccur simultaneously. dled the potential combinatorial explosion of possible hypotheses in such problems by focusing attention on a This raises the issue of estabfew “most plausible” ones. lishing what makes one hypothesis more plausible than o ...
Artificial Intelligence
... 1. If it is a win, give it the highest rating. 2. Otherwise, consider all the moves the opponent could make next. Assume the opponent will make the move that is worst for us. Assign the rating of that move to the current node. 3. The best node is then the one with the highest ...
... 1. If it is a win, give it the highest rating. 2. Otherwise, consider all the moves the opponent could make next. Assume the opponent will make the move that is worst for us. Assign the rating of that move to the current node. 3. The best node is then the one with the highest ...
Safe Artificial Intelligence and Formal Methods
... Safe Artificial Intelligence and Formal Methods (position paper) Emil Vassev ...
... Safe Artificial Intelligence and Formal Methods (position paper) Emil Vassev ...
Web Servlets and JSP
... Course Description Discover Sun’s cutting edge technologies for building backend Web applications, in a 3 days course dealing with Servlets and JSP. We begin with a quick overview of Web basics and server side programming, followed by an introduction to J2EE Web Applications and Java Servlets. We th ...
... Course Description Discover Sun’s cutting edge technologies for building backend Web applications, in a 3 days course dealing with Servlets and JSP. We begin with a quick overview of Web basics and server side programming, followed by an introduction to J2EE Web Applications and Java Servlets. We th ...
(2008) The Symbol Grounding Problem has been solved. So What`s
... be a classifier, a perceptual/pattern recognition process that operates over sensori-motor data to decide whether the object ’fits’ with the concept. If such an effective method is available, then we call the symbol grounded. There are a lot of symbols which are not about the real world but about ab ...
... be a classifier, a perceptual/pattern recognition process that operates over sensori-motor data to decide whether the object ’fits’ with the concept. If such an effective method is available, then we call the symbol grounded. There are a lot of symbols which are not about the real world but about ab ...
Cognitive architectures
... Connectionist Models Connectionist systems use statistical properties, rather than logical rules to process information to achieve effective behavior. Therefore such systems best capture the statistical regularities in training data. A prominent example for a connectionist model is the unsupervised ...
... Connectionist Models Connectionist systems use statistical properties, rather than logical rules to process information to achieve effective behavior. Therefore such systems best capture the statistical regularities in training data. A prominent example for a connectionist model is the unsupervised ...
Towards a Logic of Rational Agency
... economics [52], philosophy [17], cognitive science [73], and most recently, computer science and artificial intelligence [79]. Put crudely, an agent is an entity that is situated in some environment and is capable of acting upon it in order to modify, shape, and control it; a rational agent is one t ...
... economics [52], philosophy [17], cognitive science [73], and most recently, computer science and artificial intelligence [79]. Put crudely, an agent is an entity that is situated in some environment and is capable of acting upon it in order to modify, shape, and control it; a rational agent is one t ...
Idealizations of Uncertainty, and Lessons from Artificial Intelligence
... Human decision-making is at the core of economics. Economic models typically assume that human agents gather and process information about the alternative choices in any given situation. The information which they gather may be complete or, in an important extension of the basic theory, incomplete, ...
... Human decision-making is at the core of economics. Economic models typically assume that human agents gather and process information about the alternative choices in any given situation. The information which they gather may be complete or, in an important extension of the basic theory, incomplete, ...
Towards a Logic of Rational Agency
... economics [52], philosophy [17], cognitive science [73], and most recently, computer science and artificial intelligence [79]. Put crudely, an agent is an entity that is situated in some environment and is capable of acting upon it in order to modify, shape, and control it; a rational agent is one t ...
... economics [52], philosophy [17], cognitive science [73], and most recently, computer science and artificial intelligence [79]. Put crudely, an agent is an entity that is situated in some environment and is capable of acting upon it in order to modify, shape, and control it; a rational agent is one t ...
Using General-Purpose Planning for Action Selection in
... the social context and task state, and decides on the appropriate responses that are required to respond to users. In this system, high-level action selection is performed by a domain-independent planner which manages the interactions with customers, tracks multiple drink orders, and gathers additio ...
... the social context and task state, and decides on the appropriate responses that are required to respond to users. In this system, high-level action selection is performed by a domain-independent planner which manages the interactions with customers, tracks multiple drink orders, and gathers additio ...
Artificial intelligence
... these creatures and their fates discuss many of the same hopes, fears and ethical concerns that are presented by artificial intelligence.[6] Mary Shelley's Frankenstein,[22] considers a key issue in the ethics of artificial intelligence: if a machine can be created that has intelligence, could it al ...
... these creatures and their fates discuss many of the same hopes, fears and ethical concerns that are presented by artificial intelligence.[6] Mary Shelley's Frankenstein,[22] considers a key issue in the ethics of artificial intelligence: if a machine can be created that has intelligence, could it al ...
Artificial Intelligence
... will be complex, the foundations and the building blocks should be simple. The book works as an introductory text on AI for advanced undergraduate or graduate students in computer science or related disciplines such as computer engineering, philosophy, cognitive science, or psychology. It will appea ...
... will be complex, the foundations and the building blocks should be simple. The book works as an introductory text on AI for advanced undergraduate or graduate students in computer science or related disciplines such as computer engineering, philosophy, cognitive science, or psychology. It will appea ...
Commonsense Reasoning by Integrating Simulation and Logic
... do present a rich resource of implicit commonsense ‘know-how’. Some projects have attempted to exploit this resource indirectly [5]—placing an agent within a simulated environment to explore and learn about human settings free of the wear, cost, time and concurrency constraints of the real world. Su ...
... do present a rich resource of implicit commonsense ‘know-how’. Some projects have attempted to exploit this resource indirectly [5]—placing an agent within a simulated environment to explore and learn about human settings free of the wear, cost, time and concurrency constraints of the real world. Su ...
Preface - Beck-Shop
... Shanahan and Witkowski present a logic-based agent programming framework that allows the interleaving of planning, plan execution, and perception, and preserves reactivity. The framework is based on the event calculus. Planning and observation assimilation are viewed as abductive theorem proving tas ...
... Shanahan and Witkowski present a logic-based agent programming framework that allows the interleaving of planning, plan execution, and perception, and preserves reactivity. The framework is based on the event calculus. Planning and observation assimilation are viewed as abductive theorem proving tas ...
Introduction - The MIT Press
... (usually) known counterexamples of the concept. The task is to build a concept description from which all the previous positive instances can be rederived by universal instantiation but none of the previous negative instance (the counterexamples ) can be rederived by the same process. At this level ...
... (usually) known counterexamples of the concept. The task is to build a concept description from which all the previous positive instances can be rederived by universal instantiation but none of the previous negative instance (the counterexamples ) can be rederived by the same process. At this level ...
Brief Introduction to Educational Implications of Artificial Intelligence
... 2. You have a clearly defined goal (a desired end situation). Some writers talk about having multiple goals in a problem. However, such a multiple goal situation can be broken down into a number of single goal problems. 3. You have a clearly defined set of resources—including your personal knowledg ...
... 2. You have a clearly defined goal (a desired end situation). Some writers talk about having multiple goals in a problem. However, such a multiple goal situation can be broken down into a number of single goal problems. 3. You have a clearly defined set of resources—including your personal knowledg ...
Educators` Introduction to Machine Intelligence
... This book is designed to help preservice and inservice teachers learn about some of the educational implications of current uses of Artificial Intelligence as an aid to solving problems and accomplishing tasks. Humans and their predecessors have developed a wide range of tools to help solve the type ...
... This book is designed to help preservice and inservice teachers learn about some of the educational implications of current uses of Artificial Intelligence as an aid to solving problems and accomplishing tasks. Humans and their predecessors have developed a wide range of tools to help solve the type ...