Several members (Min Jiang, Stephen Matthews and Mike Watts) of the Social Media Subcommittee are attending the WCCI 2014 conference in Beijing. We have been Tweeting the plenaries and invited lectures that we are able to attend. Below is a summary of the highlights of Day 2 of WCCI 2014.
The first event was the plenary panel session "CI-related Research Funding", which was chaired by Marios Polycarpou. The first speaker was Marimuthu Palaniswami, who spoke about Australian research networks and their funding structure. An important point he raised was that Australian funding requires reporting of outcomes, such as what the research achieved, and how it raised the national capacity to do research. He also spoke about his seven tips for having a happy career in computational intelligence:
- Direction
- Be simple and objective
- Hunt as a pack
- Leverage your resources
- Maintain your resistance
- Demonstrate your impact
- Enjoy the experience
The next speaker was Jose Principe, who talked about his experiences over the last 25 years writing grant proposals in the USA. The messages from his talk were firstly that the rate at which US proposals are funded is so low (15%) that researchers must spend too much of their time writing proposals; secondly, computational intelligence is on the verge of making huge contributions to the world, but it is under-funded.
Paul Werbos of the US NSF followed Dr Principe, and explained that the reason so few neural network related proposals are funded is that their aren't enough proposals on neural networks. His tips for increasing your chances for getting funding from the NSF are:
- Include AIS - Adaptive and Intelligent Systems - in the title of your proposal
- Target the grand challenges in the field: cognitive optimization, prediction and big applications
- Hot topic proposals do not do well at NSF, because little is lost by not funding them
- Remember the three questions that will be asked when evaulating your proposal: What exactly will you do? How will you do it? Why is it important?
Xin Yao offered a brief response to one of the chair's first questions: what are the hot topics in CI? Xin Yao's answer: whatever you are working on at the time.
Chenghong Wang also spoke about the rate of funding of research proposals in CI in China.
Kalyan Deb gave an invited lecture about "Evolutionary Multi-Objective Optimization (EMO): Two Eventful Decades and Beyond". A great introduction to EMO was provided with easy-to-understand examples, such as the objectives involved with buying a car, i.e., bueno, bonito, barato (good, nice, cheap). A brief overview of EMO history was presented that included David Goldberg's, 1989, 10-line EMO suggestion and early EMO implementations to Deb's recent incarnation -- NSGA-III. As well as the test benchmark problems, spacecraft trajectory optimisation with University of Illinois at Urbana-Champaign and NASA-JPS and a mine scheduling application in Australia were mentioned. Research problems for the future were discussed.
Donald Wunsch gave an invited lecture about "Innovations and Open Problems in Supervised, Unsupervised and Reinforcement Learning". Donald was very enthusiastic and excited for students because they have the opportunity to embark on exciting challenges in the field. One such challenge is unified learning modalities for automatically combining supervised, reinforcement, and supervised learning without human intervention. Donald was very clear that he did not support the popular view that computers will be more intelligent than humans. In fact, Donald foresees this not even happening during our grandchildren's' lifetime - as he put it "If you expect to see robots as smart as humans in your lifetime, you're at the wrong conference, you should be at a conference on life extension".
There will be more tweets tomorrow of the panel plenary "Is "Publish or Perish" causing "Death" of science" and of several invited lectures. We'll also wrap up with another summary blog post.
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