'Causal relations' diaporamas de présentation

LECTURE 5: LAWS IN THE SOCIAL SCIENCES?

All my course outlines and PowerPoint slides can be downloaded from: http://www.freewebs.com/mphk2/ Friday, November 16 th : NO LECTURE Friday, November 23 rd : 3-4pm: Lecture 7: Practice Coffee, tea and biscuits!!! 4-5pm: Lecture 8: Values and Critical Theory. LECTURE 5:

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The causal matrix: Learning the background knowledge that makes causal learning possible

The causal matrix: Learning the background knowledge that makes causal learning possible Josh Tenenbaum MIT Department of Brain and Cognitive Sciences Computer Science and AI Lab (CSAIL). Collaborators. Tom Griffiths. Noah Goodman. Vikash Mansinghka. Charles Kemp.

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Jan Lemeire December 19 th 2007

Learning Causal Models of Multivariate Systems and the Value of it for the Performance Modeling of Computer Programs. Jan Lemeire December 19 th 2007. Supervisor: Prof. dr. ir. Erik Dirkx. Learning causal models for the performance analysis of programs executed on various computer systems.

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Causal Networks

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Presentation Objectives

Triple bottom line impacts of community energy initiatives Crossing disciplinary boundaries with Bayesian Networks Philip A Leicester BSc DIS School of Civil and Building Engineering Centre for Renewable Energy and Systems Technology Loughborough University. Presentation Objectives.

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Clarifying ideas - 1

Clarifying ideas - 1. The process of reasoning often encounters a need for clarification . Terms may be used, or claims be made, whose meaning is unclear, vague, imprecise or ambiguous. In order to evaluate an argument skilfully we must first understand it.

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Innate Knowledge of the Social World

Innate Knowledge of the Social World. Psychology Live Nov 18, 2009. Core Cognition. Object, Number, and Agent Representations. Core Cognition of Agency. Primitive Building Blocks (Fiske). Communal Sharing Equality Matching Hierarchy/Dominance. Cooperative Relations. Communal sharing

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What is Theory?

What is Theory?. Theory is NOT:. Correlation Description Interpretation Absence of data Ideology. Theory IS:. A general, abstract explanation. Theories simplify reality. The world is complex Theories tell us what to pay attention to. Theories have empirical implications.

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The Visual Causality Analyst: An Interactive Interface for Causal Reasoning

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Science powers: how Aristotelean are they?

Science powers: how Aristotelean are they?. Nancy Cartwright & John Pemberton Venice Aristotle Group, April 2014 . +. Simple science case. -. The earth has the power of gravitational attraction. When this power exercises... It PULLS the electron down.

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Investigating and preserving the essence of a destination brand - the case of Scheveningen

Investigating and preserving the essence of a destination brand - the case of Scheveningen. Johan van Rekom Erasmus Universiteit Rotterdam. Questions addressed. How can we establish which features constitute the essence of a destination brand?

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Mediating Between Causes and Probabilities: the Use of Graphical Models in Econometrics

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Overview

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Using Evolutionary Computation as a Creativity-Support Tool

Pilot. Using Evolutionary Computation as a Creativity-Support Tool. NSF CreativeIT Workshop, January 2009. Tim Chabuk University of Maryland Jason Lohn Carnegie Mellon University Derek Linden X5 Systems Jim Reggia University of Maryland. Example: Self-Replicating Machines.

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Commentary on Searle

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Zooming in on Probability and Causality (aim & preliminary results)

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Gopnik , Sobel , Schulz, & Glymour (2001) Causal learning mechanisms in very young children.

Gopnik , Sobel , Schulz, & Glymour (2001) Causal learning mechanisms in very young children. . Key insight. Theory Children build causal representations of how things work in the world. Substantive principal (top-down inferences)

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