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Introduction to AI
Introduction to AI

... ■ Transition relation: If a pair of states (S, S') is such that one move takes the system from S to S', then the transition relation is represented ...
Unit 1 Handout - Cuyamaca College
Unit 1 Handout - Cuyamaca College

... Mind: Despite a great deal of focus on behavior at various levels, we also have a sense of being. Few people conceive of themselves, their consciousness, as little more than biochemical reactions occurring within the confines of the nervous system. And it seems to most people that we’re doing more t ...
ppt - Computer Science Department
ppt - Computer Science Department

... “databases”, i.e. collections of data inference and/or estimation in statistics pattern recognition in engineering signal processing in electrical engineering ...
Neural Networks - Computer Science
Neural Networks - Computer Science

... • Pigeons were able to discriminate between Van Gogh and Chagall with 95% accuracy (when presented with pictures they had been trained on) • Discrimination still 85% successful for previously unseen paintings of the artists • Pigeons do not simply memorize the pictures • They can extract and recogni ...
slide show - Psycholosphere
slide show - Psycholosphere

... • wanting or needing to attend to something interesting, challenging, promising, or threatening; • wanting or needing to acquire knowledge or understanding; • wanting or needing to decrease cognitive dissonance, inconsistency, or uncertainty among thoughts and beliefs and associated behavior; • want ...
Editorial: Agency in Natural and Artificial Systems
Editorial: Agency in Natural and Artificial Systems

... can only be done by another agent: our claim is that we have not generated real agency yet —but how will we know we have obtained our goal? In answering this question, there is a tension between criteria that focus on the generative mechanisms and those that focus on the appeal of surface behavior. ...
The role of AI and learning
The role of AI and learning

... Distributed and parallel computations Dense connections of the basic units Connections can be modified by experience Learning is constant and (usu.) un-supervisioned Learning is based on local information ...
Application of Qualitative Reasoning to Robotic Soccer
Application of Qualitative Reasoning to Robotic Soccer

... that are caused by exogenous events like changes in illumination and sporadic misinterpretation of features. An alternative approach to modeling uncertain data is the use of probabilistic methods. However, this causes the disadvantage of having to deal with probabilities in the reasoning process. Fi ...
B - AI-MAS
B - AI-MAS

... [Georgeff, Ingrand, 1989] M. P. GEORGEFF et F. F. INGRAND. Decisionmaking in an embedded reasoning system, dans Proceedings of the Eleventh International Joint Conference on Artificial Intelligence (IJCAI89), 1989, p.972-978.  Successor of PRS: dMARS [D'Inverno, 1997] M. D'INVERNO et al. A formal s ...
Multiple linear regression used to analyse the corelation between
Multiple linear regression used to analyse the corelation between

... deviations of each data point from to the line (in case of a data point is placed on the adjustment line, the deviation is considered zero). Due to the fact that the deviations are first squared, than summed, result that there are no annulation between positive and negative values. The least squares ...
Spacecraft Magnetic Control Using Dichotomous Coordinate
Spacecraft Magnetic Control Using Dichotomous Coordinate

... types of actuators. For magnetic torquers it is not possible to provide three independent control torques at each time instant, and the behavior is time dependent because of the variations in the magnetic field along the spacecraft orbit. Therefore other actuators are used to compensate for this suc ...
Design of an efficient algorithm for fuel-optimal look-ahead
Design of an efficient algorithm for fuel-optimal look-ahead

... dimension of the state space is low. Here, an algorithm based on dynamic programming (DP) (Bellman, 1957) that finds the optimal control law is developed. Applying DP for high order systems is usually unfeasible due to exponential increase of the complexity due to the discretization of the continuou ...
Adding and Subtracting Integers and Variables
Adding and Subtracting Integers and Variables

... 5) In order to subtract a negative, you will need to model zero pairs—for example, if you are subtracting a negative 2, you can’t take the negative two away, when there isn’t anything in the negative area. So place two zero pairs on the board, that is place two below the line and two above the line ...
Partial Position Transfer in Categorical Perceptual Learning Alexander Gerganov ()
Partial Position Transfer in Categorical Perceptual Learning Alexander Gerganov ()

... (V2-V4) play a role in the changes that occur during learning even in this simple category learning scenario. Another explanation, however, could be connected to selective spatial attention (Dill, 2002). One natural way to control for attention would be to randomize the presentation of objects durin ...
VI. CASPOC-SRD: new possibilities in
VI. CASPOC-SRD: new possibilities in

... other's behavior, and therefore it is impossible to analyze the elements separately, to get the overall behavior. So, simulation of the complete drive system (which is a typical mechatronic system) has to be performed. This means that the used package have to be able to carry out the simulation of t ...
No Slide Title
No Slide Title

Neural network
Neural network

... At the end of each branch, a structure called a synapse converts the activity from the axon into electrical effects that inhibit or excite activity in the connected neurons. ...
Computer
Computer

... Early development of knowledge-based systems AI becomes an industry Neural networks return to popularity AI becomes a science The emergence of intelligent agents -- “-bots” ...
Learning nonlinear functions on vectors: examples and predictions
Learning nonlinear functions on vectors: examples and predictions

... that best describes what it does. The basal ganglia perform action selection, the prefrontal cortex plans and performs abstract thinking, and so on. In theoretical neuroscience, functions are the mathematical operations that can be combined to bring about that higher-level verbal description. While ...
Structure of Optimal Controls for a Cancer Chemotherapy Model with PK/PD
Structure of Optimal Controls for a Cancer Chemotherapy Model with PK/PD

... example [4], [11]) and have been extensively researched in the eighties and nineties (e.g. [3], [8], [9], [14], [15], [16]). However, the complexity of the underlying biological processes is difficult to capture in a mathematical framework and in many cases our understanding of the dynamics still is ...
Why do anything?  Abstract
Why do anything? Abstract

... strict in the application of such terms; for example, a mother may chide her son for “tormenting” the ant’s nest. Progress in understanding affect in terms of the information processing complexity of the behavioral control systems of the organism is required if any effort at modeling affective state ...
Failure to mobilize cognitive control for
Failure to mobilize cognitive control for

... saccades in response to the imperative stimulus resulting in faster responses and a higher error rate. Fake-Hard trials started with a cue indicating a Hard trial, but were otherwise identical to Easy trials. They were included to isolate the effects of hard vs. easy cues on activation unconfounded ...
Slot 6 LED OTM - Acuity Brands
Slot 6 LED OTM - Acuity Brands

... www.acuitybrands.com/CustomerResources/Terms_and_conditions.aspx Note: Actual performance may differ as a result of end-user environment and application. All values are design or typical values, measured under laboratory conditions at 25 °C. Specifications subject to change without notice. ...
Behavioral learning for adaptive software agents
Behavioral learning for adaptive software agents

... focus contains both the percept and relevant information from associative and episodic memories. That is, the focus holds the percept in context as CMattie currently understands it. The contents of the focus come to “consciousness” [Bogner, et al][Ramamurthy98a] when the “consciousness” mechanism br ...
A Comparative Study of Soft Computing Methodologies in
A Comparative Study of Soft Computing Methodologies in

... Fig. 2. Architecture of a 2-DOF planar manipulator ...
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Perceptual control theory

Perceptual control theory (PCT) is a model of behavior based on the principles of negative feedback, but differing in important respects from engineering control theory. Results of PCT experiments have demonstrated that an organism controls neither its own behavior, nor external environmental variables, but rather its own perceptions of those variables. Actions are not controlled, they are varied so as to cancel the effects that unpredictable environmental disturbances would otherwise have on controlled perceptions. According to the standard catch-phrase of the field, ""behavior is the control of perception"". PCT demonstrates circular causation in a negative feedback loop closed through the environment. This fundamentally contradicts the classical notion of linear causation of behavior by stimuli, in which environmental stimuli are thought to cause behavioral responses, mediated (according to Cognitive Psychology) by intervening cognitive processes.Numerous computer simulations of specific behavioral situations demonstrate its efficacy, with extremely high correlations to observational data (0.95 or better), such as are routinely expected in physics and chemistry. While the adoption of PCT in the scientific community has not been widespread, it has been applied not only in experimental psychology and neuroscience, but also in sociology, linguistics, and a number of other fields, and has led to a method of psychotherapy called the Method of Levels.PCT has roots in insights of Claude Bernard and 20th century control systems engineering and cybernetics. It was originated as such, and given its present form and experimental methodology, by William T. Powers.
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