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6.034 Artificial Intelligence. Copyright © 2004 by Massachusetts
6.034 Artificial Intelligence. Copyright © 2004 by Massachusetts

... Another way to look at the process we have just gone through is as a form of tree search. In this search space, the states are the entries in the stack, that is, the literals that appear on our stack. The edges (shown with a green dot in the middle of each edge) are the rules or facts. However, ther ...
Thinking Machines
Thinking Machines

... What is the difference between mind and brain? 1. What is intelligence? 2. Mind or Software: Computational Theory of the Mind (Abstract rules and representations) ...
Improving the Knowledge-Based Expert System Lifecycle
Improving the Knowledge-Based Expert System Lifecycle

... one manifestation of the applications that trace their roots back to those early programs. Knowledge-based expert systems are computer systems that have expertise in a given domain and are useful when analyzing and processing large amounts of data in a short amount of time [Grosan11] [Dabbaghchi97]. ...
Bayesian AI Introduction - Australasian Bayesian Network Modelling
Bayesian AI Introduction - Australasian Bayesian Network Modelling

... Applications range across the sciences, industries and government organizations. At Monash University, Bayesian AI has been used for graphical expert systems for medical diagnosis and prognosis, in meteorological predication, environmental management, intelligent tutoring systems, epidemiology, poke ...
Co-ordination in software agent systems
Co-ordination in software agent systems

... inserted to synchronise agents’ interactions appropriately. Cammarata et al [20] also employ centralised multi-agent planning in a simulated air-traffic control domain. In this demonstrator, agents (i.e. aeroplanes) in a potential conflict scenario, e.g. two aeroplanes are heading for collision, dec ...
AAAI News - Association for the Advancement of Artificial Intelligence
AAAI News - Association for the Advancement of Artificial Intelligence

... AAAI President David Waltz presented The 1999 AAAI Classic Paper Award to John McDermott for R1: An Expert in the Computer Systems Domain. sources for travel funds. AAAI membership is required for eligibility. For further information regarding the Student Volunteer Program, please contact AAAI at vo ...
Reasoning in Argumentation Frameworks Using Quantified
Reasoning in Argumentation Frameworks Using Quantified

... has been made a significant progress in the development of QBF solvers in the last few years [19]. Second, the different semantics captured by argumentation frameworks are all uniformly represented in our QBF setting. Our aim is, not at least, to illustrate how basic QBF modules can be used as build ...
An Intelligent Distributed System for Strategic Decision Making
An Intelligent Distributed System for Strategic Decision Making

... In organization theory, Mesarovic and Simon observed that lower-level decision units must be autonomous to ensure the efficiency of hierarchical organizations. Hence, the problem is how to guarantee global coherence in a system where decisions are made by different persons at different hierarchical ...
Artificial Intelligence UNIT I Page 1 of 116 CSE– Dhaanish Ahmed
Artificial Intelligence UNIT I Page 1 of 116 CSE– Dhaanish Ahmed

... often quoted: “It is not my aim to surprise or shock you-but the simplest way I can summarize is to say that there are now in the world machines that think, that learn and that create. Moreover, their ability to do these things is going to increase rapidly until-in a visible future-the range of prob ...
Discriminative Structure and Parameter Learning for Markov
Discriminative Structure and Parameter Learning for Markov

... Many new clauses are added at each step and some of them may not be useful in the long run.  Use L1-regularization to zero out those clauses  Use a state-of-the-art online L1-regularized learning algorithm named ADAGRAD_FB [Duchi et.al., 2010], a L1-regularized adaptive subgradient method. ...
Multiagent Learning: Basics, Challenges, and
Multiagent Learning: Basics, Challenges, and

... a group. In the case of competitive learning, the agents have conflicting tasks (so that not all of them can be completed, for example, due to resource limitations or because the agents’ goals are in direct opposition) and each agent’s learning goal is to ensure the best possible execution of its ...
C.V. - John P. Dickerson
C.V. - John P. Dickerson

... Toward this end, I’m building an optimization engine and cloud-based combinatorial market system for selling television advertising campaigns. Our system is in the proof-of-concept stage with one of the world’s largest cable operators (MSOs). The technology applies to cable operators (MSOs), broadca ...
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Normativity and Epistemic Intuitions
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... can be trusted?  What if my moral intuitions tell me different? Actually, another kind of answer you might give, viz., a reliabilist or consequentialist type answer, e.g., Punishing people for accidentally and non negligently causing harm does not reliably increase the amount of good in the world. ...
What is a Knowledge Representation
What is a Knowledge Representation

... The INTERNIST example also demonstrates that there is significant and unavoidable ontological commitment even at the level of the familiar representation technologies. Logic, rules, frames, etc., each embody a viewpoint on the kinds of things that are important in the world. Logic, for instance, in ...
Alan Turing`s Ten Big Ideas - Asia Pacific Math Newsletter
Alan Turing`s Ten Big Ideas - Asia Pacific Math Newsletter

... What is striking is that Turing never shared the disdain or superficial reductionism of many mathematicians. He was fascinated by the actual building of computing machines, and always willing to engage with the physicality and sheer messiness of computational processes. And this was to pay dividends ...
A Survey on Application of Bio-Inspired Algorithms
A Survey on Application of Bio-Inspired Algorithms

... with complex optimization problems and are becoming more popular nowadays. This paper surveys the recent advances in biologically inspired swarm optimization methods, including ant colony optimization algorithm, particle swarm optimization algorithm, artificial bee colony algorithm and their hybridi ...
Associative Algorithms for Computational Creativity
Associative Algorithms for Computational Creativity

... As such, we adopt the social constructivist definition of creativity that has been welldeveloped in studying human creativity (Sawyer, 2012): Creativity is the generation of an idea or artifact that is judged to be novel and also to be appropriate, useful, or valuable by a suitably knowledgeable soc ...
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s 1 - UNL CSE

... Gottlob, G., Leone, N., Scarcello, F. : On Tractable Queries and Constraints. In: 10th International Conference and Workshop on Database and Expert System Applications (DEXA 1999). (1999) Decther, R.: Constraint Processing. Morgan Kaufmann (2003) Freuder, E.C.: A Sufficient Condition for Backtrack-B ...
CV - Computer Science Intranet
CV - Computer Science Intranet

... • Journal of Decision Support Systems, Special Issue on Game Theoretic and Decision Theoretic Agents, 2003. • International Journal of Autonomous Agents and Multi-Agent Systems, Special Issue on Game Theoretic and Decision Theoretic Agents, 2002. • International Journal of Uncertainty, Fuzziness and ...
Multi-Agent Systems Introduction
Multi-Agent Systems Introduction

... Installing top-down and/or bottom-up (emergent) solving process ...
Artificial Intelligence and Expert Systems
Artificial Intelligence and Expert Systems

... by a human being, would be considered intelligent “…study of how to make computers do things at which, at the moment, people are better” (Rich and Knight [1991]) Theory of how the human mind works (Mark Fox) ...
PDF 2 of 2 - Massachusetts Institute of Technology
PDF 2 of 2 - Massachusetts Institute of Technology

... item and a different second item, but in a function, if you have the same first item then you have to have the same second item. So that means you just name the first item and then there's a unique thing that you get from applying the function. So it's OK for mother-of to be a function, discounting ...
The Limits of OCR
The Limits of OCR

... First to validate using human-factors research: – human-subject trials measuring both accuracy & tolerance – PARC’s interdisciplinary tradition: social + computer sciences ...
Lecture 11 - Chapter 7
Lecture 11 - Chapter 7

... – An organized collection of people, procedures, software, databases, and devices – Used to create, store, share, and use the organization’s knowledge and experience ...
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Ethics of artificial intelligence

The ethics of artificial intelligence is the part of the ethics of technology specific to robots and other artificially intelligent beings. It is typically divided into roboethics, a concern with the moral behavior of humans as they design, construct, use and treat artificially intelligent beings, and machine ethics, concern with the moral behavior of artificial moral agents (AMAs).
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