AISB Convention 2016

The AISB Convention is an annual conference covering the range of AI and Cognitive Science, organised by the Society for the Study of Artificial Intelligence and Simulation of Behaviour. The 2016 Convention will be held at the Uni...


Bishop and AI news

Stephen Hawking thinks computers may surpass human intelligence and take over the world. This view is based on the ideology that all aspects of human mentality will eventually be realised by a program running on a suitable compu...


Connection Science

All individual members of The Society for the Study of Artificial Intelligence and Simulation of Behaviour have a personal subscription to the Taylor Francis journal Connection Science as part of their membership. How to Acce...


Al-Rifaie on BBC

AISB Committee member and Research Fellow at Goldsmiths, University of London, Dr Mohammad Majid al-Rifaie was interviewed by the BBC (in Farsi) along with his colleague Mohammad Ali Javaheri Javid on the 6 November 2014. He was a...


Rose wins the Loebne...

After 2 hours of judging at Bletchley Park, 'Rose' by Bruce Wilcox was declared the winner of the Loebner Prize 2014, held in conjunction with the AISB.  The event was well attended, film live by Sky News and the special guest jud...


AISB Convention 2015

The AISB Convention is an annual conference covering the range of AI and Cognitive Science, organised by the Society for the Study of Artificial Intelligence and Simulation of Behaviour. The 2015 Convention will be held at the Uni...


Yasemin Erden on BBC

AISB Committee member, and Philosophy Programme Director and Lecturer, Dr Yasemin J. Erden interviewed for the BBC on 29 October 2013. Speaking on the Today programme for BBC Radio 4, as well as the Business Report for BBC world N...


Mark Bishop on BBC ...

Mark Bishop, Chair of the Study of Artificial Intelligence and the Simulation of Behaviour, appeared on Newsnight to discuss the ethics of ‘killer robots’. He was approached to give his view on a report raising questions on the et...


AISB YouTube Channel

The AISB has launched a YouTube channel: ( The channel currently holds a number of videos from the AISB 2010 Convention. Videos include the AISB round t...



AISB opportunities Bulletin Item

Summer School on Advanced Statistics and Data Mining, Madrid, SPAIN

Dear colleagues,

We would like to remind you that the early registration period for the 
summer school on 'Advanced Statistics and Data Mining' will finish on 
the 1st of june. The summer school will be organized by the Technical 
University of Madrid (UPM) between June 24th and July 5th. This year's 
programme comprises 12 courses divided into 2 weeks. Attendees may 
register in each course independently.

Early registration is now OPEN. Extended information on course 
programmes, price, venue, accommodation and transport is available at 
the school's website:

Please, send this information to your colleagues, students, and whoever 
may find it interesting.

Best regards,

Pedro Larraaga, Concha Bielza and Pedro L. Lpez-Cruz.
-- The coordinators of the school.

*** List of courses and brief description ***

* Week 1 (June 24th - June 28th, 2013) *

1st session: 9:30 - 12:30
Course 1: Bayesian networks (15 h)
       Basics of Bayesian networks. Inference in Bayesian networks. 
Learning Bayesian networks from data. Real applications.

Course 2: Statistical inference (15 h)
       Introduction. Some basic statistical test. Multiple testing. 
Introduction to bootstrap methods. Introduction to Robust Statistics.

2nd session: 13:30 - 16:30
Course 3: Supervised pattern recognition (15 h)
       Introduction. Assessing the performance of supervised 
classification algorithms. Preprocessing. Classification techniques. 
Combining multiple classifiers. Comparing supervised classification 

Course 4: Multivariate data analysis (15 h)
       Introduction. Data examination. Principal component analysis. 
Factor Analysis. Multidimensional scaling. Correspondence analysis. 
Tensor analysis. Multivariate Analysis of Variance. Canonical 
Correlation Analysis. Latent Class Analysis.

3rd session: 17:00 - 20:00
Course 5: Neural networks (15 h)
       Introduction. Perceptrons. Training algorithms. Accelerating 
convergence. Useful tricks for MLPs. Deep networks. Practical data 
modelling with neural networks.

Course 6: Feature Subset Selection (15 h)
       Introduction. Filter approaches. Wrapper methods. Embedded 
methods. Drawbacks and future strands. Practical session.

* Week 2 (July 1st - July 5th, 2013) *

1st session: 9:30 - 12:30
Course 7: Time series analysis (15 h)
       Introduction. Probability models to time series. Regression and 
Fourier analysis. Forecasting and Data mining.

Course 8: Hidden Markov Models (15 h)
       Introduction. Discrete Hidden Markov Models. Basic algorithms for 
Hidden Markov Models. Semicontinuous Hidden Markov Models. Continuous 
Hidden Markov Models. Unit selection and clustering. Speaker and 
Environment Adaptation for HMMs. Other applications of HMMs.

2nd session: 13:30 - 16:30
Course 9: Bayesian classifiers (15 h)
       Discrete predictors. Gaussian Bayesian networks-based 
classifiers. Other Bayesian classifiers. Bayesian classifiers for: 
positive and unlabeled data, semi-supervised learning, data streams, 
temporal data.

Course 10: Unsupervised pattern recognition (15 h)
       Introduction. Prototype-based clustering. Density-based 
clustering. Graph-based clustering. Cluster evaluation. Miscellanea.

3rd session: 17:00 - 20:00
Course 11: Support vector machines, regularization and convex 
optimization (15 h)
       Introduction. SVM models. SVM learning algorithms. Convex non 
differentiable optimization.

Course 12: Hot topics in intelligent data analysis (15 h)
       Multi-label and multi-dimensional classification. 
Multi-dimensional classification and multi-output regression. Advanced 
Clustering. Partially supervised classification with uncertain class 
labels. Directional statistics. Spatial point processes.