Intelligent agent - Wikipedia. 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) to distinguish them from their real world implementations as computer systems, biological systems, or organizations. 20 Inspiring Entrepreneurs Improving Health For All. Cognitive Behavioral Therapy Techniques That Work. Interview mit Klaus Theweleit. Gartner Hype Cycle For Emerging Technologies, 2016 Adds Blockchain & Machine Learning For First Time. The latest Gartner Hype Cycle for Emerging Technologies illustrates how quickly technology innovations have the potential to redefine buyer, supplier and customer relationships for any business.
Gartner added 16 new technologies to the Hype Cycle this year, including blockchain, machine learning, general purpose machine intelligence, smart workspace in addition to many others. Gartner identifies transparently immersive experiences, the perceptual smart machine age, and the platform revolution as three overarching trends that have the most potential to reshape business models, and provide enterprises with access to emerging markets and ecosystems. The Hype Cycle is based on an assessment of the market hype, maturity, business benefit and future direction of more than 2,000 technologies, grouped into 11 topic areas. The Hype Cycle for Emerging Technologies, 2016 is shown below: How cognitive computing is changing IoT. Your Garbage Data Is A Gold Mine. The Oxford Handbook of Attention, Bayesian Models of Attention. Neuroadaptive Systems: Theory and Applications. Agents that Want and Like.
Un robot motivé pour apprendre : Le rôle des motivations intrinsèques dans le développement sensorimoteur.
Les niches de progrès ne sont pas des propriétés intrinsèques de l’environnement. Elles résultent de la relation entre la structure physique du robot, les biais de ses mécanismes d’apprentissage, ses interactions passées, et l’environnement particulier dans lequel il est placé. Une fois découverte et exploitée, une niche de progrès disparaît au fur et à mesure que la situation à laquelle elle correspond devient plus prédictible. Ainsi, une trajectoire développementale, c’est-à-dire une séquence d’étapes dans lesquelles le robot se focalise sur des activités de complexité croissante, se forme sans qu’elle ait été préprogrammée par le concepteur. Il ne s’agit pas d’imiter l’homme en tout point. En modifiant l’organisation de l’espace dans lequel le robot évolue ou le type robot utilisé, il devient possible d’étudier de manière systématique le rôle respectif de l’environnement, des contraintes anatomiques et morphologiques et des dynamiques motivationnelles dans le processus de développement artificiel. Chaque trajectoire est unique, fruit d’une histoire singulière avec un environnement spécifique mais toutes les trajectoires présentent des caractéristiques structurelles communes. – weihler
4. Cliques, Clusters and Components - Social Network Analysis for Startups [Book] In the previous chapter, we mainly talked about properties of individuals in a social network.
In this chapter, we start working with progressively larger chunks of the network, analyzing not just the individuals and their connection patterns, but entire subgraphs and clusters. We’ll explore what it means to be in a triad and what benefits and stresses can come from being in a structural hole. Investors are backing more AI startups than ever before. More cars than phones were connected to cell service in Q1. Millions of people in the United States have mobile phones, and we’ve had them for years.
We may upgrade phones or change plans, but cell phones and plans are generally sold to people who already have devices. But cellular services aren’t out of new devices to connect—now they’ve got cars. In the first quarter of 2016, connected cars accounted for a third of all new cellular devices. Mobile-industry consultants at Chetan Sharma noted that there were more cars added to networks than phones and fewer tablets than previously. According to analysts, smartphone penetration is at 84% in the United States, and new customer revenue is approaching zero.
Aufmerksamkeit, Wahrnehmung, Bedeutung. Identification of psychiatric needs – psystrat. Resume first half: Neurodevelopmental Disorders Intellectual Disability: Severity is determined by adaptive functioning rather than IQ score.
Deficits in cognitive capacity beginning in the developmental period. Communication Disorders: Expressive language disorders, speech sound disorder, fluency disorder, social communication disorder (not in the presence of restricted repetitive behaviors). Using existing knowledge – psystrat. Time Pressure: Behavioral Science Considerations for Mobile Marketing. When consumers don't have a lot of time to make a decision, they tend to focus on a few key criteria or product attributes.
Behavioral economist Dan Ariely explores what this principle means for mobile marketers. Written by. Google DeepMind.
Who knows what you like can help and cure you. – weihler
Ifttt the beginning... I’d like to humbly announce that the first beta invites for a project I’m incredibly excited about are out the door.
The project is called ifttt, shorthand for “if this then that”. With this blog I hope to begin fleshing out some of the initial inspirations that led to the inception of ifttt and provide you with a taste of how ifttt can help put the internet to work for you. ERP im Kontext von Industrie 4.0. Objekte (z.
B. A New Cluster Based Fuzzy Model Tree for Data Modeling. This paper proposes a fuzzy model tree, so-called c-fuzzy model tree, consisting of local linear models using fuzzy cluster for data modeling.
Cluster centers are calculated by fuzzy clustering method using all input and output attributes. And then, linear models are constructed at internal nodes with fuzzy membership grades between centers and input attributes. The expansion of internal node is determined by comparing the error calculated at the parent node with the sum of ones at the child nodes. The Interactive Activation and Competition Network: How Neural Networks Process Information. Copyright © Simon Dennis, 1997. * These sections contain some mathematics which can be omitted on a first reading if desired.
Introduction The Interactive Activation and Competition network (IAC, McClelland 1981; McClelland & Rumelhart 1981; Rumelhart & McClelland 1982) embodies many of the properties that make neural networks useful information processing models. In this chapter, we will use the IAC network to demonstrate several of these properties including content addressability, robustness in the face of noise, generalisation across exemplars and the ability to provide plausible default values for unknown variables. The chapter begins with an example of an IAC network to allow you to see a full network in action. Towards a new mode of self-tracking.
In a conference paper and my forthcoming book The Quantified Self: A Sociology of Self-Tracking Cultures, I identify five modes of self-tracking. What I call ‘private self-tracking’ is undertaken for voluntary and personal reasons that are self-initiated. ‘Pushed self-tracking’ involves encouragement for people to monitor themselves from other agencies, while the mode of ‘communal self-tracking’ relies on people sharing their personal information with others.
‘Imposed self-tracking’ involves moving from encouragement to requiring people to collect or engage with data about themselves, so that they may have little choice in doing so. The ‘exploited self-tracking’ mode represents the ways in which personal data may be used by other actors and agencies for their own purposes, either overtly or covertly. Like this: E-cockpit. Herbert A. Simon.