HLC

Human-Like Computing Third Wave of AI Workshop (3AI-HLC 2019)


As part of the EPSRC funded Human-Like Computing Network+ we are organising a workshop on Third Wave Artificial Intelligence on Friday 26th April 2019 from 09:30 – 17:00.

Third wave AI is DARPA's term for its upcoming programme of research in areas which go beyond the limitations of first wave AI and second wave.

First Wave AI (1970s – 1990s) is defined as good at reasoning, but no ability to learn or generalize. Second Wave AI (2000s to present) is defined as good at learning and perceiving, but minimal ability to reason or generalize.

Third Wave AI (est 2020s – 2030s) is envisaged as consisting of excellent at perceiving, learning and reasoning, and able to generalize with the following attributes:

•    Contextual adaptation, able to explain decisions.
•    Can converse in natural language.
•    Requires far fewer data samples for training.
•    Able to learn and function with minimal supervision.

The purpose of the EPSRC funded Human-Like Computing Network+ is to support the development of a UK-wide multi-disciplinary community of researchers within the EPSRC Priority area of Human-Like Computing (HLC). The main stakeholders in our project are: other researchers within both Artificial Intelligence and Cognitive Science both nationally and internationally.  See our website (hlc.doc.ic.ac.uk) for further details.

Participation

This workshop is meant as an opportunity to exchange ideas and present recent work on an important and timely topic in AI. We welcome presentations by experienced as well as early researchers. We encourage two types of presentations:  short (10 minutes) and long (20 minutes). You can also express your interest to participate without presenting by submitting a short description of your research (see below).

Online registration is now closed, please contact Bridget Gundry (bridget.gundry@imperial.ac.uk) if you want to register for the workshop after the closing date.


Programme

Friday 26th April 2019 – Huxley Lecture Theatre 308, Imperial College London

 

Session 1
 Invited Talks - Chair: Prof Alan Bundy

09:30 – 09:45

Welcome & Introduction
Prof Nick Jennings, Vice-Provost (Research and Enterprise), Imperial College London

09:45 – 10:20

Prof Stephen Muggleton, Dept. of Computing,  Imperial College London, "What do we need from Third Wave Artificial Intelligence?"

10:20 – 11:00

Prof Francesca Toni, Dept. of Computing, Imperial College London, "Extracting Dialogical Explanations for Review Aggregations with Argumentative Dialogical Agents"

11:00 – 11:20

Coffee break / poster session (Room 217/218)

11:20 – 12:00

 Prof Ute Schmid, Cognitive System Group, University of Bamberg, "Cooperative Learning with Mutual Explanations"

12:00 – 12:40

Prof Nick Chater, Warwick Business School,  University of Warwick, "Virtual bargaining: A microfoundation for the theory of social interaction"

12:40 – 13:30

Lunch / poster session (Room 217/218)

13:30 – 14:00

Prof Murray Shanahan, Google DeepMind, "Reconciling Deep Learning with Symbolic AI"

14:00 – 14:40

Prof Kristian Kersting, Dept. of Computer Science, Technische Universitไt Darmstadt, "Deep Machines That Know When They Do not Know"
 
Session 2
 Long Presentations - Chair: Prof Stephen Muggleton

14:40 – 15:00

Jingqing Zhang and Piyawat Lertvittayakumjorn and Yike Guo, Department of Computing, Imperial College London, "Integrating Semantic Knowledge to Tackle Zero-shot Text Classification"

15:00 – 15:20

 Mark Law, Alessandra Russo and Krysia Broda,
Department of Computing, Imperial College London, "Inductive Learning of Answer Set Programs"

15:20 – 15:40

Coffee break / poster session  (Room 217/218)

15:40 – 16:00

Michael Zbyszynski, Atau Tanaka and Balandino Di Donato, Goldsmiths, University of London, "Real-time, interactive machine learning in musical performance"

16:00 – 16:20

Artur d’Avila Garcez, Department of Computer Science, City, University of London, "Neural-Symbolic Systems for Software Model Evolution, Run-Time Monitoring and Property Learning"
Session 3 Short Presentations - Chair: Prof Artur d’Avila Garcez

16:20 – 16:30

Lewis Hammond and Vaishak Belle
The University of Edinburgh, "Deep Tractable Probabilistic Models for Moral Responsibility"

16:30 – 16:40

C้line Hocquette and Stephen Muggleton,
Department of Computing, Imperial College London, "Can Meta-Interpretive Learning outperform Deep Reinforcement Learning of Evaluable Game strategies?"
16:40 – 16:50 Piyawat Lertvittayakumjorn and Francesca Toni,
Department of Computing, Imperial College London, "Interpreting CNNs for Text Classification"
16:50 – 17:00 Stassa Patsantzis, Department of Computing, Imperial College London, "Metasplain - Assigning meaningful names to invented predicates"

17:00 – 17:10

Discussion/Closing Remarks