Building agents from shared ontologies through apprenticeship
... ontology that defines and organizes the concepts from the application domain, and a set of problem solving rules expressed in terms of these concepts. The process of building this knowledge base starts with creating a domain ontology by importing concepts from the shared ontologies of an OKBC server ...
... ontology that defines and organizes the concepts from the application domain, and a set of problem solving rules expressed in terms of these concepts. The process of building this knowledge base starts with creating a domain ontology by importing concepts from the shared ontologies of an OKBC server ...
BAVRD2015-Short Program - Vision Science at UC Berkeley
... Lyndia Wu Investigating the relationship between head impact kinematics and oculomotor response – a pilot study Christy Sheehy Usages of the Tracking Scanning Laser Ophthalmoscope ...
... Lyndia Wu Investigating the relationship between head impact kinematics and oculomotor response – a pilot study Christy Sheehy Usages of the Tracking Scanning Laser Ophthalmoscope ...
Resources - CSE, IIT Bombay
... A search needs to be carried out to find which point in the image of L corresponds to which point in R. Naively carried out, this can become an O(n2) process where n is the number of points in the retinal images. ...
... A search needs to be carried out to find which point in the image of L corresponds to which point in R. Naively carried out, this can become an O(n2) process where n is the number of points in the retinal images. ...
Softcomputing Techniques for Improved Electroencephalogram
... activities and modeling of electrical impulses of the human brain can be significantly improved using these techniques or a hybrid thereof. Keywords: electroencephalogram (EEG), Genetic Algorithm, Artificial Neural Network, Fuzzy systems, clinical diagnosis. 1. Introduction A. Softcomputing and gene ...
... activities and modeling of electrical impulses of the human brain can be significantly improved using these techniques or a hybrid thereof. Keywords: electroencephalogram (EEG), Genetic Algorithm, Artificial Neural Network, Fuzzy systems, clinical diagnosis. 1. Introduction A. Softcomputing and gene ...
Pattern Recognition and Feed-forward Networks
... Historically feed-forward networks were introduced as models of biological neural networks (McCulloch and Pitts, 1943), in which nodes corresponded to neurons and edges corresponded to synapses, and with an activation activation function g(a) given by a simple threshold. The recent development of f ...
... Historically feed-forward networks were introduced as models of biological neural networks (McCulloch and Pitts, 1943), in which nodes corresponded to neurons and edges corresponded to synapses, and with an activation activation function g(a) given by a simple threshold. The recent development of f ...
JARINGAN SYARAF TIRUAN
... In principle, they can do anything a symbolic/logic system can do, and more. (In practice, getting them to do it can be rather difficult…) ...
... In principle, they can do anything a symbolic/logic system can do, and more. (In practice, getting them to do it can be rather difficult…) ...
pre02
... • Switched Capacitor (SC) is a circuit made of one capacitor and two switches which connect the capacitor with a given frequency alternately to the input an output of the SC. This simulates the behaviors of a resistor, so SCs are used in integrated circuits instead of resistors. The resistance is se ...
... • Switched Capacitor (SC) is a circuit made of one capacitor and two switches which connect the capacitor with a given frequency alternately to the input an output of the SC. This simulates the behaviors of a resistor, so SCs are used in integrated circuits instead of resistors. The resistance is se ...
Nick Gentile
... – Pattern recognition - “The task performed by a network trained to respond when an input vector close to a learned vector is presented. The network “recognizes” the input as one of the original target vectors.” – Error vector - “The difference between a network’s output vector in response to an inp ...
... – Pattern recognition - “The task performed by a network trained to respond when an input vector close to a learned vector is presented. The network “recognizes” the input as one of the original target vectors.” – Error vector - “The difference between a network’s output vector in response to an inp ...
Talk title: Creative Cognitive Systems Ana
... Computational creativity focuses on implementing and evaluating artificial creative systems, while human creative cognition approaches center on working to understand the processes and types of representations humans use when being creative or creatively problem solving. An interdisciplinary cogniti ...
... Computational creativity focuses on implementing and evaluating artificial creative systems, while human creative cognition approaches center on working to understand the processes and types of representations humans use when being creative or creatively problem solving. An interdisciplinary cogniti ...
Why a computer is known as data processor
... A computer is known as a data processor because it accepts data, stores data, process data according to a set of instructions, and also retrieve the data when required. In essence it accepts and stores input data, processes them and produces results under the direction of step by step program. Any P ...
... A computer is known as a data processor because it accepts data, stores data, process data according to a set of instructions, and also retrieve the data when required. In essence it accepts and stores input data, processes them and produces results under the direction of step by step program. Any P ...
Introduction to Machine Learning. - Electrical & Computer Engineering
... – Database mining and knowledge discovery in databases (KDD) – Computer inference: learning to reason ...
... – Database mining and knowledge discovery in databases (KDD) – Computer inference: learning to reason ...
Hierarchy of Languages
... A Decidable Language is one that is recognized by a Turing Machine which halts on all input strings. A Semidecidable Language is one that is recognized by a Turing Machine which halts on all input strings which are in the language, but may loop infinitely on some strings which are not in the languag ...
... A Decidable Language is one that is recognized by a Turing Machine which halts on all input strings. A Semidecidable Language is one that is recognized by a Turing Machine which halts on all input strings which are in the language, but may loop infinitely on some strings which are not in the languag ...
neural network
... For example, shooting is partly about knowing where to aim, and partly about the skill required to aim properly ...
... For example, shooting is partly about knowing where to aim, and partly about the skill required to aim properly ...
DEPARTMENT MANAGERS
... By the end of the course, the student will be able to: 1. understand information needs of an organisation, department or functional division, and individual stakeholders involved in the business; 2. gain a sound theoretical knowledge of decision support, data mining and data warehousing principles; ...
... By the end of the course, the student will be able to: 1. understand information needs of an organisation, department or functional division, and individual stakeholders involved in the business; 2. gain a sound theoretical knowledge of decision support, data mining and data warehousing principles; ...
WSD: bootstrapping methods
... – Or derive the co-occurrence terms automatically from machine readable dictionary entries – Or select seeds automatically using co-occurrence statistics (see Ch 6 of J&M) ...
... – Or derive the co-occurrence terms automatically from machine readable dictionary entries – Or select seeds automatically using co-occurrence statistics (see Ch 6 of J&M) ...
1996TuringIntro
... the ability to learn from contact with human beings and to “adapt to their standards”. Michie points out that learning from humans is far from straightforward - typically as humans acquire expertise in a particular domain they become progressively less rather than more able to articulate their knowl ...
... the ability to learn from contact with human beings and to “adapt to their standards”. Michie points out that learning from humans is far from straightforward - typically as humans acquire expertise in a particular domain they become progressively less rather than more able to articulate their knowl ...
Neurobiologically Inspired Robotics: Enhanced Autonomy through
... Neurobiologically inspired robotics goes by many names: brainbased devices, cognitive robots, neurorobots, and neuromorphic robots, to name a few. The field has grown into an exciting area of research and engineering. The common goal is twofold: Firstly, developing a system that demonstrates some le ...
... Neurobiologically inspired robotics goes by many names: brainbased devices, cognitive robots, neurorobots, and neuromorphic robots, to name a few. The field has grown into an exciting area of research and engineering. The common goal is twofold: Firstly, developing a system that demonstrates some le ...
H AAAI-98 Robot Exhibition July 28-30, 1998, Madison, Wisconsin Call for Participation
... ave you wanted to bring a robot to the National Conference on Artificial Intelligence, but don’t have the resources to devote to programming a contest entry? Does your robot hardware not fit into the competition tasks? Do you want to enter the contest, but would also like to demonstrate the other wo ...
... ave you wanted to bring a robot to the National Conference on Artificial Intelligence, but don’t have the resources to devote to programming a contest entry? Does your robot hardware not fit into the competition tasks? Do you want to enter the contest, but would also like to demonstrate the other wo ...
WORD - Semiosis Evolution Energy
... self-organized, i.e., the result of adaptation in interaction with an environment, rather than programmed or built-in by a designer, and thus often not even interpretable to humans (cf. Prem 1995). Hence, unlike computer programs, their genesis typically can not be explained with reference to human ...
... self-organized, i.e., the result of adaptation in interaction with an environment, rather than programmed or built-in by a designer, and thus often not even interpretable to humans (cf. Prem 1995). Hence, unlike computer programs, their genesis typically can not be explained with reference to human ...
A Case for Computer Brain Interfaces
... One method scientists are studying to enhance human cognition is through direct computer-brain interfaces (Kennedy). While the concept may seem outlandish, rudimentary brain prostheses have been in use for over forty years (Chivukula et al.). The computer-brain link in widest spread use is currently ...
... One method scientists are studying to enhance human cognition is through direct computer-brain interfaces (Kennedy). While the concept may seem outlandish, rudimentary brain prostheses have been in use for over forty years (Chivukula et al.). The computer-brain link in widest spread use is currently ...
Cai, D.; Tao, L.; Rangan, A.; McLaughlin, D. Kinetic Theory for Neuronal Network Dynamics. Comm. Math. Sci 4 (2006), no. 1, 97-12.
... networks, the article is concerned with the development of representations for simulating more efficient the dynamics of large multi-layered networks. Starting with networks of conductance-based integrate-and-fire (I&F) neurons, a full kinetic description without introduction of new parameters is de ...
... networks, the article is concerned with the development of representations for simulating more efficient the dynamics of large multi-layered networks. Starting with networks of conductance-based integrate-and-fire (I&F) neurons, a full kinetic description without introduction of new parameters is de ...
Computational Thinking and CS Unplugged
... includes (but is not limited to) the following characteristics: ...
... includes (but is not limited to) the following characteristics: ...