ECCO Home | ecco.vub.ac.be Intelligent agent Simple reflex agent Intelligent agents are often described schematically as an abstract functional system similar to a computer program. For this reason, intelligent agents are sometimes called abstract intelligent agents (AIA)[citation needed] to distinguish them from their real world implementations as computer systems, biological systems, or organizations. Intelligent agents are also closely related to software agents (an autonomous computer program that carries out tasks on behalf of users). A variety of definitions[edit] Intelligent agents have been defined many different ways.[3] According to Nikola Kasabov[4] IA systems should exhibit the following characteristics: Structure of agents[edit] A simple agent program can be defined mathematically as an agent function[5] which maps every possible percepts sequence to a possible action the agent can perform or to a coefficient, feedback element, function or constant that affects eventual actions: Classes of intelligent agents[edit]
Quand la publicité détourne mèmes et culture web Depuis quelques années, les mèmes ont réussi à s'imposer parmi les codes les plus tenaces du net. Ces derniers incarnent un phénomène particulier décliné en masse, pour devenir à terme un code connu de tous avec ses propres caractéristiques. Une sorte de blague à grande échelle sur la toile. Dit comme ça ce n'est pas très clair, mais il existe des centaines de mèmes, tous repris dans la bible du genre : Know Your Meme. Comme toute bonne tendance populaire et numérique, la publicité s'est empressée au fur et à mesure des mois de reprendre ces mèmes pour les utiliser à des fins commerciales. Parfois c'est très réussi, d'autres fois un peu plus à la traîne, mais quelques annonceurs se risquent au jeu. Les mèmes "purs"Double Rainbow En janvier 2010, un utilisateur de Youtube a mis en ligne une vidéo de lui dans un pur moment extase devant un phénomène scientifique (plus ou moins) rare : un double arc-en-ciel. Plus de 33 millions de vues Ben &Jerry's comme un clin d'oeil humoristique Derp ! David
Future Scenarios What Will The Internet Look Like In 10 Years? The Internet Society engaged in a scenario planning exercise to reveal plausible courses of events that could impact the health of the Internet in the future. While obviously not intended to be a definitive overview of the landscape or all potential issues, we believe the results are interesting and, we hope, thought-provoking. We are sharing them in the hope that they will inspire thought about possibilities for the future development of the Internet, and involvement in helping to make that happen in the best possible way. Future Scenario Resources Besides viewing the video scenarios below, you can: Common Pool Scenario Link to transcript of video Positive “generative” and “distributed & decentralised” properties. Boutique Networks Scenario Link to transcript of video Moats and Drawbridges Scenario Link to transcript of video Porous Garden Scenario Link to transcript of video
The Singularity Is Near The Singularity Is Near: When Humans Transcend Biology is a 2005 non-fiction book about artificial intelligence and the future of humanity by inventor and futurist Ray Kurzweil. This is his first book to embrace the Singularity as a term, but the ideas contained within are derived from his previous books, the The Age of Spiritual Machines (1999) and The Age of Intelligent Machines (1990). Kurzweil describes his law of accelerating returns which predicts an exponential increase in technologies like computers, genetics, nanotechnology, robotics and artificial intelligence. Kurzweil has been criticized for extrapolating current trends without bounds, when in fact exponential growth often tapers off as resources are exhausted. Content[edit] Exponential growth[edit] Kurzweil characterizes evolution throughout all time as progressing through six epochs, each one building on the next. Computational capacity[edit] Moore's Law The brain[edit] Exponential Growth of Computing The Singularity[edit]
Monitoring and Surveillance Agents Monitoring and surveillance agents (also known as predictive agents) are a type of intelligent agent software that observes and reports on computer equipment. Monitoring and surveillance agents are often used to monitor complex computer networks to predict when a crash or some other defect may occur. Another type of monitoring and surveillance agent works on computer networks keeping track of the configuration of each computer connected to the network. It tracks and updates the central configuration database when anything on any computer changes, such as the number or type of disk drives. Examples[edit] NASA's Jet Propulsion Laboratory has an agent that monitors inventory, planning, and scheduling equipment ordering to keep costs down.Allstate Insurance has a network with thousands of computers. Haag & Cummings & McCubbrey & Pinsonneault & Donovan (2006). See also[edit]
JULIEN BOYÉ - BLOG Julien Boyé - L’histoire (vraie) de minutebuzz.com En Juin nous nous rencontrons pour la première fois avec Maxime lors d’un petit déjeuner de passage à Paris à l’aéroport CDG. Nous étions tous les deux excités et avions immortalisé cette rencontre par une photo. L’erreur que j’ai pu commettre fut de partir à New York pour l’été, travaillant à distance tous les jours sur MinuteBuzz mais cela ne vaut pas une présence à Paris auprès de l’équipe (Soraya et Maxime qui gère la rédaction par facebook) installés à l’époque dans les locaux de MaxiCours (société de Patrice Magnard). Le froid entre Maxime et moi a donc commencé ce jour là. Etait-ce en lien avec le succès de minutebuzz ? Au mois de Juillet il souhaite que Laure Lefèvre, une personne qui travaillait dans la même société que lui en tant que consultante, rejoigne l’équipe. Nous avons donc à ce moment là signé les documents nécessaires à la création de la société et j’ai quitté le projet comme actionnaire de la société et fondateur caché. Ma plus grosse erreur a été : À très vite.
SIN Graph - Countdown to SIN Logarithmic Chart Countdown to Singularity, Events expressed as Time before Present (Years) on the X axis and Time to Next Event (Years) on the Y axis, Logarithmic Plot Page 17, Linear Plot page 18. Source: M.T. Rosing, "13C-Depleted carbon microparticles in >3700-Ma sea-floor sedimentary rocks from west greenland," Science 283.5402 (January 29, 1999): 674-6, See also H. Furnes et al., "Early life recorded in archean pillow lavas," Science 304.5670 (April 23, 2004):578-81; M.T. Rosing, "Early Archaean oxygenic photosynthesis - The observational approach," Geophysical Research Abstracts 7.11202 (2005); W. Altermann and J. B. Y Kimura, "Examining time trends in the Oldowan technology at Beds I and II, Olduvai Gorge," Journal of Human Evolution 43.3 (September 2002):291-321. A.M. Dennis O'Neil, " Evolution of Modern Humans: Early Archaic Homo sapiens," T.D. D. O. H. Cuneiform Digital Library Initiative E.
The best visuals to explain the Singularity to senior executives Tomorrow morning I’m doing a presentation to the top executive team of a very large organization on the next 20 years. Most of what I will cover will be general societal, business and technological drivers as well as specific strategic issues driving their business. However as part of stretching their thinking I’ll also speak a about the Singularity. As such I’ve been trying to find one good image to introduce my explanation, however I haven’t been able to find one which is quite right for the purpose. Ray Kurzweil’s Six Epochs diagram below is great and the one I’ll probably end up using, however it is a bit too over-the-top for most senior executives. Source: Ray Kurzweil, Applied Abstractions The chart below from Hans Moravec showing how exponential growth of computing power will allow machines to match human intellectual capabilities is excellent, but it is seriously out of date. Source: Hans Moravec, When will computer hardware match the human brain? Source: Ray Kurzweil, Tropophilia
Multi-agent system Simple reflex agent Learning agent Concept[edit] Multi-agent systems consist of agents and their environment. Agents can be divided into different types: Very simple like: passive agents[6] or agent without goals (like obstacle, apple or key in any simple simulation)Active agents[6] with simple goals (like birds in flocking, or wolf–sheep in prey-predator model)Or very complex agents (like cognitive agent, which contain complex calculations) Environment also can be divided into: Virtual EnvironmentDiscrete EnvironmentContinuous Environment Characteristics[edit] The agents in a multi-agent system have several important characteristics:[10] Autonomy: the agents are at least partially independent, self-aware, autonomousLocal views: no agent has a full global view of the system, or the system is too complex for an agent to make practical use of such knowledgeDecentralization: there is no designated controlling agent (or the system is effectively reduced to a monolithic system)[11] Properties[edit]