Monthly Archives: June 2016
The Research Centre for Machine Learning (RCML) at City is pleased to announce the seminar by Dr. Luis Lamb – Professor and Dean (Director) of the Institute of Informatics (2011-2015 & 2015-2019), ex officio (2011-2015 & 2015-2019) and Elected (2010-2012) Member of the University Council at the Federal University of Rio Grande do Sul, Porto Alegre, Brazil..
Please find below the details of the talk:
Venue: A108 (College Building)
Date & Time: Jun 24, 2016 (12:00-13:00)
Title: Learning and Reasoning in AI and Cognitive Computation
Abstract: Cognitive Computation and Artificial Intelligence have received increasing interest from both academics and relevant industries. The recent impact of AI and machine learning applications have led many to question the future influence that these research fields may have upon human life. Moreover, several leading scientists and intellectuals have voiced concerns about possible consequences of Artificial Intelligence, Cognitive Computing and Machine Learning. In this talk, we highlight recent developments on the research towards the integration of robust reasoning and learning mechanisms in cognitive computing and AI and the impact that these fields may have in the near future.
Speaker Bio: Luis Lamb is Professor and Dean (Director) of the Institute of Informatics (2011-2015 & 2015-2019), ex officio (2011-2015 & 2015-2019) and Elected (2010-2012) Member of the University Council at the Federal University of Rio Grande do Sul, Porto Alegre, Brazil. He was Deputy Dean of the Institute of Informatics at UFRGS from August 2006 to October 2011.
He holds both the Ph.D. in Computing Science from the Imperial College London (2000) and the Diploma of the Imperial College (D.I.C.) (2000), MSc by research (1995) and BSc in Computer Science (1992) from the Federal University of Rio Grande do Sul, Brazil. In 2010 he received the MIT Executive Certificate in Strategy and Innovation and in 2014 he received the Executive Certificate in Management and Leadership (Massachusetts Institute of Technology – Sloan School of Management). He is Honorary Visiting Fellow at the Department of Computing, City University London and Visiting Research Fellow, Abductive Systems Group, Department of Philosophy, University of British Columbia, Canada (group led by John Woods).
His research interests include: Logic in Computer Science and Artificial Intelligence, Neural Computation; Social Computing and Computing in the Physical and Social Sciences. Lamb has co-authored two research monographs: Neural-Symbolic Cognitive Reasoning, with d’Avila Garcez and Gabbay (Springer 2009) and Compiled Labelled Deductive Systems, with Broda, Gabbay and Russo (IoP 2004). He is co-editor-in-chief of the Revista de Informática Teórica e Aplicada and he is on the editorial board of the Logic Journal of the IGPL (Oxford) and of the Journal of the Brazilian Computer Society (Springer). Lamb’s research has led to publications in ACM Transactions on Autonomous and Adaptive Systems, Behavioral and Brain Sciences, Theoretical Computer Science, Neural Computation, Journal of Logic and Computation, IEEE Transactions on Neural Networks and Learning Systems, Physica A, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, The Journal of Theoretical Biology, and at the flagship Artificial Intelligence and Neural Computation conferences AAAI, IJCAI, NIPS, HCOMP. His research on embedded systems software modelling and adaptation has led to publications at ICSE-11, ASE2010, and DATE2008. He was co-organizer of the Dagstuhl Seminar 14381: Neural-Symbolic Learning and Reasoning in September 2014. He is, or has been, member of the Programme or Organizing Committee of a large number of international conferences and workshops on Artificial Intelligence, Neural and Cognitive Computation, Logic in Computer Science, Embedded Systems and Formal Methods. Lamb holds an Advanced Research Fellowship (2010-2017) from the Brazilian National Research Council CNPq. He is a professional member of the ACM, ACM SIGACT, AAAI, AMS, ASL, IEEE, C&GCA, and the Brazilian Computer Society.
The Research Centre for Machine Learning (RCML) at City is pleased to announce the seminar by Dr. Lucian Busoniu – associate professor with the Department of Automation at the Technical University of Cluj-Napoca.
Please find below the details of the talk:
Venue: AG21 (College Building)
Date & Time: Jun 30, 2016 (12:00-13:00)
Title: Planning Methods for Near-Optimal Nonlinear Control
Abstract: We propose an optimistic planning method to search for near-optimal sequences of actions in discrete-time, infinite-horizon optimal control problems with discounted rewards. The dynamics are nonlinear, while the action is continuous and lies in a bounded interval. The method works like model-based predictive control, but exploits insights from bandit theory in reinforcement learning to run the search. Specifically, it iteratively refines adaptive-dimensionality hyperboxes, always choosing an optimistic box with the largest upper bound on the rewards. Under certain Lipschitz conditions on the dynamics and rewards, a guaranteed near-optimality bound is obtained as a function of the computation invested. We also give an empirical extension that does not require knowing the Lipschitz constants, and works much better in experiments, strongly indicating that such a method is the best next step.
Speaker Bio: Lucian Busoniu received the Ph.D. degree (cum laude) from the Delft University of Technology, the Netherlands, in 2009. He is an associate professor with the Department of Automation at the Technical University of Cluj-Napoca, and has previously held research positions in the Netherlands and France. His research interests include planning for nonlinear optimal control, reinforcement learning and approximate dynamic programming, multiagent systems, and robotics. He received the 2009 Andrew P. Sage Award for the best paper in the IEEE Transactions on Systems, Man, and Cybernetics.
We are very happy to announce that Srikanth Cherla passed his PhD viva (with minor amendments recommended by the examiners) on the 25th of May, 2016. The topic of his thesis is “Neural Probabilistic Models for Melody Prediction, Sequence Labelling and Classification”.
Srikanth is currently working as a Machine Learning Engineer at Jukedeck.
Many congratulations and all the very best to him from the group!