'Finite time' presentation slideshows

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Developing Behavioral Persistence Through the Use of Intermittent Reinforcement

Developing Behavioral Persistence Through the Use of Intermittent Reinforcement

Developing Behavioral Persistence Through the Use of Intermittent Reinforcement. Chapter 6. Definitions. Schedule of reinforcement – rule specifying which occurrences of a given behavior, if any, will be reinforced Continuous Reinforcement (CRF):

By boaz
(559 views)

Don’t Do It Like ME! Setting Realistic Short-Term Goals

Don’t Do It Like ME! Setting Realistic Short-Term Goals

Don’t Do It Like ME! Setting Realistic Short-Term Goals. Stacey Schultz-Cherry Associate Member Department of Infectious Diseases, St. Jude Children’s Research Hospital. Are you kidding?. What do other people do?. Undergrads. What’s a . What’s a short- term goal?. What’s a . Hmmmm?.

By orville
(153 views)

Supergranulation Scale Solar Surface Convection Simulations

Supergranulation Scale Solar Surface Convection Simulations

Supergranulation Scale Solar Surface Convection Simulations. progress report . Dali Georgobiani Michigan State University Presenting the results of Bob Stein (MSU) & Åke Nordlund (Denmark) with David Benson (Kettering University). Numerical Method. Staggered mesh

By mliss
(188 views)

Zeno's Paradox

Zeno's Paradox

Zeno's Paradox. Slides prepared by: Pamela Leutwyler,    Professor of Mathematics   Bucks County Community College. The hare and the tortoise decide to race. Since I run twice as fast as you do, I will give you a half mile head start. Thanks! . ½ . ¼ . ½ . ¼ .

By jerzy
(130 views)

Snap-Stabilizing Detection of Cutsets

Snap-Stabilizing Detection of Cutsets

HIPC’2005, December 18-21 2005, Goa (India). Snap-Stabilizing Detection of Cutsets. Alain Cournier, Stéphane Devismes , and Vincent Villain. What is a Cutset?. Let G=(V,E) be an undirected connected graph. Let CS be a subset of V. Let G’ be the subgraph induced by V\CS .

By lazaro
(114 views)

El Problema de la Creación de Hipótesis en el Método Científico-Experimental Hipotético-Deductivo

El Problema de la Creación de Hipótesis en el Método Científico-Experimental Hipotético-Deductivo

El Problema de la Creación de Hipótesis en el Método Científico-Experimental Hipotético-Deductivo. Historia y Filosofía de la Ciencia Antonio Núñez, ULPGC. Newton. Hactenus phænomena cælorum & maris nostri per vim gravitatis exposui, sed causam gravitatis nonum assignavi...

By anson
(124 views)

Manifestly Retarded Formalism for Out-of-Equilibrium Thermal Field Theories I. Dadić Ruđer Bošković Institute, Zagreb

Manifestly Retarded Formalism for Out-of-Equilibrium Thermal Field Theories I. Dadić Ruđer Bošković Institute, Zagreb

Manifestly Retarded Formalism for Out-of-Equilibrium Thermal Field Theories I. Dadić Ruđer Bošković Institute, Zagreb Talk given at “ 2nd Croatian – Hungarian Meeting” , 30. August -3. September , 2007., Rab, Croatia. R/A formalism in early 1990ies

By roseanne
(147 views)

Paradoxes

Paradoxes

Paradoxes. Prepared by L. Gilmore. What is it?. A paradox is an argument where the premises, if true, infers a conclusion that is a contradiction. Paradoxes are self contradictory because they often contains statements that are both true, but cannot be true at the same time.

By karlyn
(175 views)

Intro to Logic

Intro to Logic

Intro to Logic. Propositional logic. Inference Rules. First-order Logic. Logic Proofs & Deduction. Use re-write rules to “deduce” from what is known to what is unknown. These rules can be quite complex. This idea can be used to create Automatic Theorem Provers . Limitations.

By indiya
(105 views)

March 05, 2009

March 05, 2009

100g. Toy Ball Mission Profile Toy Ball Integration & Structural Analysis ‘Fallback’ Lunar Circularization Concept. March 05, 2009. [1]. Toy Ball (100g payload). Design at 90% completion! Mass: 2.52kg Power: 0.9984Wh upon arrival (Self-Sufficient)

By cleary
(123 views)

B alancing R educes A symptotic V ariance of O utputs

B alancing R educes A symptotic V ariance of O utputs

B alancing R educes A symptotic V ariance of O utputs. Yoni Nazarathy * EURANDOM, Eindhoven University of Technology, The Netherlands. Based on some joint works with Ahmad Al Hanbali , Michel Mandjes , Gideon Weiss and Ward Whitt. QTNA 2010, Beijing, July 26, 2010.

By dayton
(78 views)

Homework 3: Transfer Function to State Space

Homework 3: Transfer Function to State Space

Chapter 4. Realization of State Space Equations. Homework 3: Transfer Function to State Space. Find the state-space realizations of the following transfer function in Frobenius Form , Observer Form , and Canonical Form .

By yestin
(448 views)

Development of Problem Solving Ability

Development of Problem Solving Ability

Development of Problem Solving Ability. Class Starter Questions answer in your journal (entry #6). What does cognitive development mean? What has a child learned when he or she understands object permanence ? At what age do children learn the principle of conservation of liquid volume?

By lily
(66 views)

BIG BANG

BIG BANG

BIG BANG. EVIDENCE FOR BIG BANG. Hot Big Bang Model:. The universe began expanding a finite time ago from a very dense , very hot initial state. Dense = particles packed close together. Hot = particles moving rapidly. As space expanded, the universe became lower in density and colder .

By adlai
(275 views)

Directed Triangular Formations

Directed Triangular Formations

Supelec EECI Graduate School in Control. Directed Triangular Formations . A. S. Morse Yale University. Gif – sur - Yvette May 24, 2012. TexPoint fonts used in EMF. Read the TexPoint manual before you delete this box.: A A A A A A A A A A A A A A A A A. FORMATION CONTROL.

By suzuki
(102 views)

Butterfly chaos

Butterfly chaos

Eman Abu S umra. Butterfly chaos. Physics department , faculty of science An- Najah National University Nablus, Palestine. Contents. Introduction Chaos definition and characteristics of chaos History of chaos Butterfly effect Butterfly chaos theory

By shadow
(423 views)

Dynamic Programming

Dynamic Programming

Dynamic Programming. A typical infinite horizon problem. (1). (2). (Intertemporal constraint.). (3). (Initial condition.). State. xt. Control. ut. Value function. Finite time horizon example. Hamilton-Jacobi-Bellman equation. Solution Method. (1) Backward induction.

By shing
(142 views)

Flows and Networks (158052)

Flows and Networks (158052)

Introduction to theorie of flows in complex networks: both stochastic and deterministic apects Size 5 ECTS 16 lectures : 8 by R.J. Boucherie focusing on stochastic networks 8 by W. Kern focusing on deterministic networks Common problem

By quana
(109 views)

Takeshi Morita Tata Institute of Fundamental Research

Takeshi Morita Tata Institute of Fundamental Research

Resolution of the singularity in Gregory-Laflamme transition through Matrix Model. Takeshi Morita Tata Institute of Fundamental Research. based on collaboration with M. Mahato, G. Mandal and S. Wadia. (work in progress). Introduction and Motivation.

By jarah
(103 views)

Co-design Finite State Machines

Co-design Finite State Machines

Co-design Finite State Machines. Many slides of this lecture are borrowed from Margarida Jacome. Summary of Dataflow Network Model. Partially ordered tags Explicit concurrency Blocking read (non-reactive) Fundamentally deterministic No input or output choice. Summary of FSM. Reactive

By zasha
(106 views)

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