Forum for Artificial Intelligence Research
(FAIR) 2016

CAUSALITY:
Bayesian Networks as Platform for Knowledge Representation in Science and Philosophy

28-30 November 2016, Stellenbosch University, JH Neethling Building, Victoria Street

About FAIR

Welcome to the website of the 5th Forum for Artificial Intelligence Research Summer School (FAIR 2016), to be held from 28-30 November 2016 at Stellenbosch University, South Africa. FAIR is the annual summer school organised by the Centre for Artificial Intelligence Research, and is aimed at students and researchers in Knowledge Acquisition, Representation, Transfer and Application.

Click here to register for FAIR 2016. Please note that registration is free of charge but space is limited, so please register as soon as possible.

invited speakers


Dr. GREGOR PAVLIN
Senior Researcher and Program Manager
Thales Nederland B.V., D-CIS Lab


Dr. ROLAND POELLINGER
Munich Center for Mathematical Philosophy (MCMP)

Programme

MONDAY

TIME

TOPIC

SPEAKER

09:00 – 10:30

1. Decoding Cause and Effect

Propensity, probability, regularity, correlation, counterfactuals, and mechanisms

Roland Poellinger (MCMP)

Break

11:00 – 12:30

2: Causal Graphs and Interventions

Causes as difference-makers, Bayesian networks and interventions, inferred causation and algorithmic aspects, type vs token and the actual cause, modularity (and criticism)

Roland Poellinger (MCMP)

Lunch

13:30 – 15:00

3: Causal Paradox and the Concept of Event

Causal decision theory, Newcomb’s problem and prisoners’ dilemma, the concept of event and Cambridge change variables, quantum mechanics and locality

Roland Poellinger (MCMP)

Break

15:30 – 16:30

4: Bayesian network tutorial

Introduction

Software: Hugin Lite

Alta de Waal (UP)


TUESDAY

TIME

TOPIC

SPEAKER

09:00 – 10:30

5: Causal Hypotheses and Evidence Amalgamation

Bayesian epistemology, Bayesian confirmation, evidence and evidence amalgamation, application: encoding the Hill guidelines for the assessment of causality in pharmacology

Roland Poellinger (MCMP)

Break

11:00 – 12:30

6: Bayesian networks, ontologies and Description Logics

Ontologies and Bayesian networks

Bayesian Networks and Description Logics

Applications of Bayesian Networks


Deshen Moodley (UCT)

Tommie Meyer (UCT)

Alta Da Waal (UP)

Lunch

13:30 – 15:00

7: Distributed reasoning systems (DRS)

  • Introduction and applications of DRS

  • Bayesian networks as appropriate technology for DRSs

  • Design process

  • Lessons learnt

Gregor Pavlin (Thales Research and Technology, The Netherlands)

Break

15:30 – 16:30

8: Distributed reasoning system case study

Gregor Pavlin & Deshen Moodley


WEDNESDAY

TIME

TOPIC

SPEAKER

09:00 – 10:30

9: Introduction to Causal Models and Bayesian networks

  • Reasoning under uncertainty

  • Causality

  • Conditional independence assumption

    • Markov blanket

    • d-separation

  • Learning of Bayesian networks

  • Inference with Bayesian networks

    • Types of reasoning

Alta de Waal (University of Pretoria)

Break

11:00 – 12:30

10: Particle filters as a special case of Bayesian networks

  • Theory – Structure and parameterisation

  • Applications of particle filters

Gregor Pavlin (Thales Research and Technology, The Netherlands)

Lunch


Click here to download the FAIR 2016 programme.
Click here to download the reading material for Roland Poellinger's seminars.