Original file was NineWaysToFriendlyAI_v6.tex
... The problem of formally or at least very carefully defining the goal of Friendliness has been considered from a variety of perspectives. Among a list of fourteen objections to the Friendly AI concept, with suggested answers to each, Sotala (2011) includes the issue of friendliness being a vague conc ...
... The problem of formally or at least very carefully defining the goal of Friendliness has been considered from a variety of perspectives. Among a list of fourteen objections to the Friendly AI concept, with suggested answers to each, Sotala (2011) includes the issue of friendliness being a vague conc ...
Applications of Preferences using Answer Set Programming
... we would like to express the fact that we are more interested in answer sets containing than answer sets containing . Then, we would expect to obtain only f g. In order to specify a preference ordering among the answer sets of a program with respect to an ordered list of atoms, we propose to use dou ...
... we would like to express the fact that we are more interested in answer sets containing than answer sets containing . Then, we would expect to obtain only f g. In order to specify a preference ordering among the answer sets of a program with respect to an ordered list of atoms, we propose to use dou ...
Towards a Computational Model of Analogical Arguments
... The result of the studies of analogical arguments that we have outlined here, present several problems for current computational models. First, it is clear that people can understand analogical arguments though, as we have seen, they do not find them especially more convincing than a straight factua ...
... The result of the studies of analogical arguments that we have outlined here, present several problems for current computational models. First, it is clear that people can understand analogical arguments though, as we have seen, they do not find them especially more convincing than a straight factua ...
Artificial Intelligence and Humor
... 1. Ritchie, G. 2001. Current Directions in Computational Humour. Artif. Intell. Rev. 16, 2 (Oct. 2001), 119-135. DOI= http://dx.doi.org/10.1023/A:1011610210506 2. Christian F. Hempelmann, Victor Raskin and Katrina E. Triezenberg. “Computer, Tell Me a Joke ... but Please Make it Funny: Computational ...
... 1. Ritchie, G. 2001. Current Directions in Computational Humour. Artif. Intell. Rev. 16, 2 (Oct. 2001), 119-135. DOI= http://dx.doi.org/10.1023/A:1011610210506 2. Christian F. Hempelmann, Victor Raskin and Katrina E. Triezenberg. “Computer, Tell Me a Joke ... but Please Make it Funny: Computational ...
A Concise Introduction To Multiagent Systems And Distributed
... brachman series editor thomas dietterich series editor, a concise introduction to multiagent systems and - a concise introduction to multiagent systems and distributed artificial intelligence english 2007 isbn 1598295268 84 pages pdf 1 mbmultiagent systems is an, a concise introduction to multiagen ...
... brachman series editor thomas dietterich series editor, a concise introduction to multiagent systems and - a concise introduction to multiagent systems and distributed artificial intelligence english 2007 isbn 1598295268 84 pages pdf 1 mbmultiagent systems is an, a concise introduction to multiagen ...
Machine Learning I - Mit - Massachusetts Institute of Technology
... Another learning problem, familiar to most of us, is learning motor skills, like riding a bike. We call this reinforcement learning. It's different from supervised learning because no-one explicitly tells you the right thing to do; you just have to try things and see what makes you fall over and wha ...
... Another learning problem, familiar to most of us, is learning motor skills, like riding a bike. We call this reinforcement learning. It's different from supervised learning because no-one explicitly tells you the right thing to do; you just have to try things and see what makes you fall over and wha ...
the excerpt from a UBS CIO WM
... Odyssey have shown the extreme potential of AI, most of that remains imagination. Despite research for more than five decades, the real progress on AI has been witnessed only in the recent past. We believe AI is divided broadly into three stages: artificial narrow intelligence (ANI), artificial gene ...
... Odyssey have shown the extreme potential of AI, most of that remains imagination. Despite research for more than five decades, the real progress on AI has been witnessed only in the recent past. We believe AI is divided broadly into three stages: artificial narrow intelligence (ANI), artificial gene ...
Bayesian Reasoning - Bayesian Intelligence
... There is little doubt that an AI will need to be able to reason logically. An inability to discover, for example, that a system’s conclusions have reached inconsistency is more likely to be debilitating than the discovery of an inconsistency itself. For a long time there has also been widespread rec ...
... There is little doubt that an AI will need to be able to reason logically. An inability to discover, for example, that a system’s conclusions have reached inconsistency is more likely to be debilitating than the discovery of an inconsistency itself. For a long time there has also been widespread rec ...
FREE Sample Here
... D) Green computing is not a realistic choice for homeowners due to extra equipment that is needed to make it worthwhile. Answer: D Diff: 2 Ref: Objective 7 Explain the terms "ubiquitous computing" and "convergence" 39) Everyday tasks, such as turning on a light switch, bring us into contact with com ...
... D) Green computing is not a realistic choice for homeowners due to extra equipment that is needed to make it worthwhile. Answer: D Diff: 2 Ref: Objective 7 Explain the terms "ubiquitous computing" and "convergence" 39) Everyday tasks, such as turning on a light switch, bring us into contact with com ...
6.034 Artificial Intelligence. Copyright © 2004 by Massachusetts
... We've now spent a fair bit of time learning about the language of first-order logic and the mechanisms of automatic inference. And, we've also found that (a) it is quite difficult to write first-order logic and (b) quite expensive to do inference. Both of these conclusions are well justified. Theref ...
... We've now spent a fair bit of time learning about the language of first-order logic and the mechanisms of automatic inference. And, we've also found that (a) it is quite difficult to write first-order logic and (b) quite expensive to do inference. Both of these conclusions are well justified. Theref ...
A Review of Human Activity Recognition Methods
... is free to perform an activity. The development of a fully automated human activity recognition system, capable of classifying a person’s activities with low error, is a challenging task due to problems, such as background clutter, partial occlusion, changes in scale, viewpoint, lighting and appeara ...
... is free to perform an activity. The development of a fully automated human activity recognition system, capable of classifying a person’s activities with low error, is a challenging task due to problems, such as background clutter, partial occlusion, changes in scale, viewpoint, lighting and appeara ...
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 ...
... 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 ...
CS2053
... 5. Davis E.Goldberg, “Genetic Algorithms: Search, Optimization and Machine Learning”, Addison Wesley, N.Y., 1989. 6. S. Rajasekaran and G.A.V.Pai, “Neural Networks, Fuzzy Logic and Genetic Algorithms”, PHI, 2003. 7. R.Eberhart, P.Simpson and R.Dobbins, “Computational Intelligence - PC Tools”, AP Pro ...
... 5. Davis E.Goldberg, “Genetic Algorithms: Search, Optimization and Machine Learning”, Addison Wesley, N.Y., 1989. 6. S. Rajasekaran and G.A.V.Pai, “Neural Networks, Fuzzy Logic and Genetic Algorithms”, PHI, 2003. 7. R.Eberhart, P.Simpson and R.Dobbins, “Computational Intelligence - PC Tools”, AP Pro ...
teză de doctorat - AI-MAS
... Faculty of Computer Science and Automatic Control Computer Science Ph.D. Artificial Emotion Simulation Techniques for Intelligent Virtual Characters by M.Sc. Valentin Lungu ...
... Faculty of Computer Science and Automatic Control Computer Science Ph.D. Artificial Emotion Simulation Techniques for Intelligent Virtual Characters by M.Sc. Valentin Lungu ...
Ruinous Arguments: Escalation of disagreement and the dangers of
... will often try to put forward qualifications of their position to clarify why accepting such a common ground does not commit them to yielding to the opponent’s claim. The very fact that complex instances of argumentation involve scores of sub-arguments indicates that the original disagreement has bi ...
... will often try to put forward qualifications of their position to clarify why accepting such a common ground does not commit them to yielding to the opponent’s claim. The very fact that complex instances of argumentation involve scores of sub-arguments indicates that the original disagreement has bi ...
Evolutionary algorithms
... Evolutionary optimization v.s. machine learning [Computing machinery and intelligence. Mind 49: 433-460, 1950.] “We cannot expect to find a good child machine at the first attempt. One must experiment with teaching one such machine and see how well it learns. One can then try another and see if it ...
... Evolutionary optimization v.s. machine learning [Computing machinery and intelligence. Mind 49: 433-460, 1950.] “We cannot expect to find a good child machine at the first attempt. One must experiment with teaching one such machine and see how well it learns. One can then try another and see if it ...
AMC - Queen Mary University of London
... In her seminal book The Creative Mind, Margaret Boden [2004] identifies three different types of creativity, relative to the notion of the conceptual space which contains all the concepts of a particular kind: combinatorial, exploratory, and transformational. Combinatorial creativity, similar in pri ...
... In her seminal book The Creative Mind, Margaret Boden [2004] identifies three different types of creativity, relative to the notion of the conceptual space which contains all the concepts of a particular kind: combinatorial, exploratory, and transformational. Combinatorial creativity, similar in pri ...
Reasoning with Axioms: Theory and Practice
... experiments with implementations have shown that, for reasons of (lack of) efficiency, they are highly unsatisfactory as a practical methodology for reasoning with DL terminologies. Firstly, experiments with the Kris system have shown that integrating unfolding with the (tableaux) satisfiability alg ...
... experiments with implementations have shown that, for reasons of (lack of) efficiency, they are highly unsatisfactory as a practical methodology for reasoning with DL terminologies. Firstly, experiments with the Kris system have shown that integrating unfolding with the (tableaux) satisfiability alg ...
Narrative Intelligence - Carnegie Mellon School of Computer Science
... but it does not know what other behaviors are possible and why it was chosen instead of them. In most behavior-based architectures, behaviors simply do not know enough about other behaviors to be able to express their interrelationships to the user. In this light, classical AI would seem to have an ...
... but it does not know what other behaviors are possible and why it was chosen instead of them. In most behavior-based architectures, behaviors simply do not know enough about other behaviors to be able to express their interrelationships to the user. In this light, classical AI would seem to have an ...
Combinations of Case-Based Reasoning with Other Intelligent Methods (short paper)
... CBR with other intelligent methods. Such combinations are becoming increasingly popular due to the fact that in many application domains a vast amount of case data is available. Such combined approaches have managed to solve problems in application domains where a case-based module needs the assista ...
... CBR with other intelligent methods. Such combinations are becoming increasingly popular due to the fact that in many application domains a vast amount of case data is available. Such combined approaches have managed to solve problems in application domains where a case-based module needs the assista ...
Mining Key Skeleton Poses with Latent SVM for Action Recognition
... with well-designed handcrafted features. Recently, with the developing of deep learning, several Recurrent Neural Networks (RNN) models have been proposed for action recognition. In order to recognize actions according to the relative motion between limbs and the trunk, [18] uses an end-to-end hiera ...
... with well-designed handcrafted features. Recently, with the developing of deep learning, several Recurrent Neural Networks (RNN) models have been proposed for action recognition. In order to recognize actions according to the relative motion between limbs and the trunk, [18] uses an end-to-end hiera ...
Artificial Intelligence – Agents and Environments
... tenuous, something that is essentially a personal construct – within our own minds – so it never can be completely defined to suit everyone (see Chapter 9 for further explanation). Artificial Intelligence researchers also like to perform “thought experiments”. These are shown as follows: ...
... tenuous, something that is essentially a personal construct – within our own minds – so it never can be completely defined to suit everyone (see Chapter 9 for further explanation). Artificial Intelligence researchers also like to perform “thought experiments”. These are shown as follows: ...
Proceedings of the Seventh Int’l Conf. on Artificial Intelligence and Expert... San Francisco, November, 1995.
... in CLOS using a three-phase discrete event simulation [3] algorithm. The simulator was implemented as two main layers. The first layer consists of a general object-oriented discrete event simulator with classes defined to represent customers, servers, queues, etc. The second layer is domain-specific ...
... in CLOS using a three-phase discrete event simulation [3] algorithm. The simulator was implemented as two main layers. The first layer consists of a general object-oriented discrete event simulator with classes defined to represent customers, servers, queues, etc. The second layer is domain-specific ...
Cyberfeminism and Artificial Life
... nor static. The ‘science wars’, based on the history of two cultures competing for a singular idea of value (Snow 1998 [1959]) and perpetuated by old fashioned institutional rivalry and insecurity (Gross and Levitt 1998 [1994]) are nothing if not futile. This is shown most clearly in the debates on ...
... nor static. The ‘science wars’, based on the history of two cultures competing for a singular idea of value (Snow 1998 [1959]) and perpetuated by old fashioned institutional rivalry and insecurity (Gross and Levitt 1998 [1994]) are nothing if not futile. This is shown most clearly in the debates on ...
Dialogue Tools and Negotiation Support Systems in a Three-Step
... Although some systems operating on small, straightforward legal domains proved successful, the AI & Law community realized that developing legal expert systems was far more complicated than it first appreciated. In an attempt to solve complex issues such as how legal reasoning and argumentation coul ...
... Although some systems operating on small, straightforward legal domains proved successful, the AI & Law community realized that developing legal expert systems was far more complicated than it first appreciated. In an attempt to solve complex issues such as how legal reasoning and argumentation coul ...
Philosophy of artificial intelligence
The philosophy of artificial intelligence attempts to answer such questions as: Can a machine act intelligently? Can it solve any problem that a person would solve by thinking? Are human intelligence and machine intelligence the same? Is the human brain essentially a computer? Can a machine have a mind, mental states and consciousness in the same sense humans do? Can it feel how things are?These three questions reflect the divergent interests of AI researchers, cognitive scientists and philosophers respectively. The scientific answers to these questions depend on the definition of ""intelligence"" and ""consciousness"" and exactly which ""machines"" are under discussion.Important propositions in the philosophy of AI include:Turing's ""polite convention"": If a machine behaves as intelligently as a human being, then it is as intelligent as a human being. The Dartmouth proposal: ""Every aspect of learning or any other feature of intelligence can be so precisely described that a machine can be made to simulate it."" Newell and Simon's physical symbol system hypothesis: ""A physical symbol system has the necessary and sufficient means of general intelligent action."" Searle's strong AI hypothesis: ""The appropriately programmed computer with the right inputs and outputs would thereby have a mind in exactly the same sense human beings have minds."" Hobbes' mechanism: ""Reason is nothing but reckoning.""↑ ↑ ↑ ↑ ↑ ↑