The AI seminar on 7th Dec 2023 will feature Prof Simon Dobson who will be talking about “Some stuff about sheaves”.
The seminar will be at 11am in JCB1.33a.
If you would like to join online, please email rh347@st-andrews.ac.uk for a link to the call.
Thank you to Professor Gordon Blair for delivering this year’s distinguished lecture on Computer Science and the environment.
The series of talks explained the role of computer science in addressing the massive challenges associated with a changing climate.
Feedback was positive and the series was enjoyed by all!
From Left to Right: Jonathan Lewis, Blesson Varghese, Simon Dobson, Gordon Blair, Ian Miguel & Al Dearle (Back)
We had our first School seminar of the semester today. The speaker was André G. Pereira visiting Scotland on a SICSA DVF Fellowship. André is working on AI Planning problems, an area that is closely related to the work of our own Constraint Programming research group.
Title: Understanding Neuro-Symbolic Planning
Abstract: In this seminar, we present the area of neuro-symbolic planning, introducing fundamental concepts and applications. We focus on presenting recent research on the problem of learning heuristic functions with machine learning techniques. We discuss the distinctions and particularities between the “model-based” and “model-free” approaches, and the different methods to address the problem. Then, we focus on explaining the behavior of “model-free” approaches. We discuss the generation of the training set, and present sampling algorithms and techniques to improve the quality of the training set. We also discuss how the distribution of samples over the state space of a task, together with the quality of its estimators, are directly related to the quality of the learned heuristic function. Finally, we empirically detail which factors have the greatest impact on the quality of the learned heuristic function.
Biography: Dr. André G. Pereira is a professor at the Federal University of Rio Grande do Sul, Brazil. His research aims to develop and explain the behavior of intelligent systems for sequential decision-making problems. Dr. Pereira has authored several papers on top-tier venues such as IJCAI, AAAI, and ICAPS. These papers contribute towards explaining the behavior of heuristic search algorithms, how to use combinatorial optimization-based reasoning to solve planning tasks, and how to use machine learning techniques to produce heuristic functions. Dr. Pereira is a program committee member of IJCAI and AAAI. His doctoral dissertation was awarded second place in the national Doctoral Dissertation Contest on Computer Science (2017), and first place in the national Doctoral Dissertation Contest on Artificial Intelligence (2018). Dr. Pereira advised three awarded students on national events, including first place and finalist in the Scientific Initiation Work Contest (2018, 2022), and finalist in the Master Dissertation Contest on Artificial Intelligence (2020).
The Systems Research Group is re-starting their seminars series from 6th May 2022. Seminars will take place every two weeks at 1pm, on Fridays. From May to July the seminars will be online (SRG Teams), while from September onward we aim to move them to a hybrid format. More information on the schedule can be found on the seminars page of the Systems Research Group site.
As part of the schools Distinguished Lecture Series we look forward to welcoming Prof. Giovanna Di Marzo Serugendo on Tuesday 9 November.
Prof. Giovanna Di Marzo Serugendo received her Ph.D. in Software Engineering from the Swiss Federal Institute of Technology in Lausanne (EPFL) in 1999. After spending two years at CERN (the European Center for Nuclear Research) and 5 years in the UK as Lecturer, she became full professor at the University of Geneva in 2010. Since 2016, she is the Director of the Computer Science Center of the University of Geneva, Switzerland. She has been nominated in 2018 among the 100 digital shapers in Switzerland. Her research interests relate to the engineering of decentralised software with self-organising and emergent behaviour. This involves studying natural systems, designing and developing artificial collective systems, and verifying reliability and trustworthiness of those systems. Giovanna co-founded the IEEE International Conference on Self-Adaptive and Self-Organising Systems (SASO) and the ACM Transactions on Autonomous Adaptive Systems (TAAS), for which she served as EiC from 2005 to 2011.
This event will be held on Teams with further details to follow.
The second school seminar on 5th November at 2pm, on Teams. If you do not have the Teams link available please contact the organiser, Ian Gent.
Details TBA.
RESCHEDULED: please note the changed date and a non-standard time!
Abstract: Prest is a recently published piece of open-source software for computational revealed preference analysis that provides novel ways to estimate decision makers’ preferences over choice alternatives by analysing their observable choice behaviour. This software is informed by classic as well as recent developments in economic revealed preference theory. Some of the recent developments take the form of models that are computationally complex. This complexity currently hinders the inclusion of these models in the Prest toolkit. The presentation will first aim to describe the primary ideas underpinning Prest and illustrate them with examples from its existing toolkit. It will then proceed with a discussion of some of the challenges pertaining to the expansion of that toolkit with more models and operations. The presentation will be self-contained and no prior background in economics will be necessary.
Speaker Bio: Georgios is a Reader in Economics at the University of St Andrews, working mainly on decision theory and revealed preference analysis. In the latter research programme, Georgios’ work aims to improve our understanding of people’s decision processes and preferences through theoretical, experimental/empirical as well as computational methods. Georgios co-developed the Prest software program for computational revealed preference analysis (https://prestsoftware.com/).
Abstract: Innovation and creativity are the research drivers of the Human-Computer Interaction (HCI) community which is currently investing a vast amount of resources in the design and evaluation of “new” user interfaces and interaction techniques, leaving the correct functioning of these interfaces at the discretion of the helpless developers. In the area of formal methods and dependable systems the emphasis is usually put on the correct functioning of the system leaving its usability to secondary-level concerns (if at all addressed). However, designing interactive systems requires blending knowledge from these domains in order to provide operators with enjoyable, usable and dependable systems. The talk will present possible research directions and their benefits for combining several complementary approaches to engineer interactive critical systems. Due to their specificities, addressing this problem requires the definition of methods, notations, processes and tools to go from early informal requirements to deployed and maintained operational interactive systems. The presentation will highlight the benefits of (and the need for) an integrated framework for the iterative design of operators’ procedures and tasks, training material and the interactive system itself. The emphasis will be on interaction techniques specification and validation as their design is usually the main concern of HCI conferences. A specific focus will be on automation that is widely integrated in interactive systems both at interaction techniques level and at application level. Examples will be taken from interactive cockpits on large civil commercial aircrafts (such as the A380), satellite ground segment application and Air Traffic Control workstations.
Speaker Bio: Dr. Philippe Palanque is Professor in Computer Science at the University Toulouse 3 “Paul Sabatier” and is head of the Interactive Critical Systems group at the Institut de Recherche en Informatique de Toulouse (IRIT) in France. Since the late 80s he has been working on the development and application of formal description techniques for interactive system. He has worked for more than 10 years on research projects to improve interactive Ground Segment Systems at the Centre National d’Etudes Spatiales (CNES) and is also involved in the development of software architectures and user interface modeling for interactive cockpits in large civil aircraft (funded by Airbus). He was involved in the research network HALA! (Higher Automation Levels in Aviation) funded by SESAR programme which targets at building the future European air traffic management system. The main driver of Philippe’s research over the last 20 years has been to address in an even way Usability, Safety and Dependability in order to build trustable safety critical interactive systems. He is the secretary of the IFIP Working group 13.5 on Resilience, Reliability, Safety and Human Error in System Development, was steering committee chair of the CHI conference series at ACM SIGCHI and chair of the IFIP Technical Committee 13 on Human-Computer Interaction.
Abstract: In this talk, I will present a case study to illustrate how automated algorithm configuration can be used to gain insights into theoretical results on an evolutionary algorithm, namely the (1+(λ,λ)) Genetic Algorithm. This work is a collaboration with Carola Doerr.
The (1+(λ,λ)) Genetic Algorithm is an evolutionary algorithm that has interesting theoretical properties. It is the first algorithm where the benefit of crossover operator is rigorously proved. It is also the first example where self-adjusting parameter choice is proved to outperform any static parameter choice. However, it is not very well understood how the hyper-parameter settings influences the overall performance of the algorithm. Analyzing such multi-dimensional dependencies precisely is at the edge of what running time analysis can offer. In this work, we make a step forward on this question by presenting an in-depth study of the algorithm’s hyper-parameters using techniques in automated algorithm configuration.
Speaker bio: Dr Nguyen Dang is a post-doc in the Constraint Programming group at the University of St Andrews. Her main research focus is on automated algorithm configuration, algorithm selection and their applications in various contexts. These techniques make use of statistical methods and machine learning for fine-tuning of algorithm parameters, assessing parameters’ importance and building algorithm portfolios. Another line of her research is about solving combinatorial optimisation problems using metaheuristic algorithms.
