Kung Pow Chicken recipe I learned from Ermo and helped make with Leslie at his and Shu’s place today. It was soooo sooo delicious!
4 chicken thighs cut into tiny-ish cubes. Best if thigh is still somewhat frozen. It is easier to cut.
Mix up the marinade for the chicken. Some salt, soy sauce, vinegar, sugar, and corn starch (mixed with a bit of water). Basically this is done without any measuring. You do it to how you like it. So, if you like it salty then more salt and soy sauce. If you like it a bit bitter have more vinegar. If you like a bit sweet and salty have more sugar. Basically you have a bowl and you use a ladle and you pour those ingredients into the ladle and you use that to measure and mix.
Once you get it how you like it mix it into the chicken and let it sit for 20 minutes.
While that is sitting get your spices together. Numb spice you just buy already and don’t do anything. The chilli peppers you may have whole and you just use kitchen shears to cut tiny lengths. Then chop up onion sprouts and a few cloves of garlic to your liking. Also pour out some peanuts. Can just use unsalted peanuts from the store.
By now the twenty minutes is probably up and you can heat oil in a wok on high and once the oil is very hot put the cut up chicken into the pan. Stir vigorously keeping the chicken moving and flipping. A sort of stir flip motion continuously. Do this until you start to see the chicken change from pink to white. Once that happens immediately take the chicken off the heat and put it onto a plate. You may pour off any of the excess juice to either save or throw away.
Now turn the heat to a medium temperature and add in some oil again. Let it heat up. Then add in the numb spice and chili pepper and stir them around until it smells good and the garlic is looking nice. Then add back in the chicken. Turn up the heat a bit. And then add in the onion sprouts and peanuts. This part you must continue the stir and flip motion vigorously until the chicken is mixed in with the other ingredients and appears to be fully cooked. Note that this does not take very long.
You can eat this by itself or if you want can serve with some rice.
Also, the cool part about this is that it is highly dependent on what you like and what tastes good to you. So, there really is no wrong way to make kung pow chicken. You could add other vegetables if you want or leave out some of the spice if you think it is too spice.
The IROS paper was submitted 10 minutes before the deadline on March 1st. The paper was okay, but I’m not thrilled about it because it is only the beginning stages of the work. So, it doesn’t really use the bounty hunting stuff to its fullest. Future papers will hopefully provide that. We also had to create a video. Ermo and I got the footage of the Pioneer doing the visual servoing on the ball both indoors and semi-successfully outdoors (either due to lighting or to the massively long ping times was not able always stop in time before running into the ball).
Now that is over I’m taking a bit of a break from working with robots and am working with Ermo to do some research in continuous action multiagent learning (CAMAL our acronym, don’t steal it!). It has been a ton of fun! I’ve been doing derivations and learning new math (and re-learning some old math!). Getting to work out how the equations and proofs of convergence happen I believe will aid me in my work with doing proofs of convergence with bounty hunting in the future. So, it is benefiting Ermo and me at the same time and we are having fun in the process :)! We are working on this for a paper in NIPS. If our algorithm concept is successful and we can show some convergence we should have a very strong NIPS paper. David is also trying to join in and we can greatly use his help as it is a very challenging problem. Main issue is he is still taking classes. Can’t wait for his classes to be done!
Dan wants us to write up a paper for the Robocup Symposium on how we were able to adjust the behaviors to work with a robot that could not turn that well using HiTAB (our learning from demonstration software). That is due March 25! He just told us about it this monday. Thankfully though we won’t have to produce any experiments or results we just need to write about what we did. So we are actually pushing that off until the 22nd because Ermo and I need to make a poster and a slide for GMU’s first CS symposium. Just what we need, not! The really frustrating part is that it is mandatory for all CS PhD students to attend and those selected to present are required to present! So, it is not optional. I guess they figured no one would show up otherwise.
I got the rejection email from AAMAS last week for my paper on task abandonment for my bounty hunting system. However, I sort of was expecting this as it needs some more theoretical basis. So, I have to work on that.
In the mean time there is still IROS! That is in Korea :). The paper is due March 1st and I just started working on getting the code written for that. But this is a fun paper as it is combining cloud robotics (can’t stand that name!) and my bounty hunting work. So, I’m giving myself a lightning fast tutorial on ROS, raspberry pi, and the pioneer 3dx robot! Plan is to get the base system working by friday so next week we can start doing experiments and collecting results. Then the week before the paper is due we can write it! So, I think we will have just enough time to pull it off. At least this paper seems likely to be accepted as it both cloud robotics and bounty hunting are very cutting edge and putting it all on an actual robot should seal the deal :)! So, hopefully I’ll be going to Korea in October!
I think I’d like to make a gyroscope if I end up going to the fab lab at gmu. Here is the link to one that includes design documents for one.
I found this journal Practical Applications of Agents and Multi-Agent Systems and their list of publications and conference proceedings here. They look like a very neat conference. I took a look at their most recent proceedings and found to my delight that they have some cool applications that I’m interested in and make me think that some of my ideas for applications for the Bounty system aren’t so bad.
First, I think that my idea for using the bounty system for reducing traffic problem in an earlier post might be a good one (here and maybe here but it seems like maybe they could be developed a bit more). Or at least that the bounty model should be applied. I found the paper, From Goods to Traffic: First Steps Toward an Auction-Based Traffic Signal Controller, that was published this year in paamas which shows that there is some interest in using these sorts of methods.
The other idea I had a while back was to use the bounty system for parking (here)! They have a paper, Evaluating the Social Benefit of a Negotiation–Based Parking Allocation, which looks into the problem of parking in cities and methods for doing this and how it can help both the city and the drivers. So, again there is a body of work (they cite) that is interested in this problem.
Maybe I should put together some of my ideas for applying bounties to these problems and try and publish them there? Also, I’m excited to find out what other problems that paamas has published. Glad I found this and can’t wait for the semester to begin :).
I think I should start a MAS/MRS reading group. CMU had/has a nice website detailing their MAS/MRS reading group.
It looks like it would have been really fun to have gone to those. So, might as well have it at GMU!
I’m planning my directed reading class this coming semester. So, basically I have/get to come up with an entire semester’s worth of material. I might be able to make a class out of it by the time I’m done 🙂 haha. My subjects are focusing on the areas I want to explore with the bounty hunting task allocation model.
- Petri-net models and applications to MAS and task allocation. Basically I’m thinking that petri-nets can be used to create task allocation problems abstractly. By doing so I can better gauge the usefulness of different task allocation methods.
- Contest Theory and tournament theory. They are two areas which seem like they have crucial information for helping the bounty hunting method mature. Explore how aspects such as effort can be incorporated into the task allocation problem to make it more realistic.
- Coalitional Game theory and the El Farol Bar problem. The game theory aspect will help me create better learning algorithms for the bounty hunters and the El Farol problem is very similar to the bounty hunting problem. Also, look into collectives, a complex systems term that describes a system of selfish agents that have a well defined system level performance measure.
- Specific problems in Multiagent Task Allocation. Namely cooperative, resource dependent, heterogeneous tasks and tasks that have sub-tasks.
- Automated Task decomposition for MAS. This is mainly so that I can explore the idea that behaviors (and possibly tasks) may be automatically reduced to states with single feature transitions hierarchically using only state action pair sequences. Doing so will allow complex behaviors to be learned without so much work required by the human to decompose the problem. I’d also like to apply it to tasks.
- Learning coalition formation, or automatic organization formation for MAS mainly with coordination in mind. Main applications focusing on large scale systems like autonomous vehicles, cloud robotics and crisis management.
- Large scale MAL/MAS and applications. autonomous vehicles, cloud robotics and crisis management
- Current topics in reinforcement learning and its use in MAS.
I’m working on fleshing out the details before the semester starts so that I might already have the list of papers I want to read.
A bunch of us from GMU were Botball mentors for middle schools in the DC area. I helped out at Fred Lynn middle school with Kevin, David, Joseph and Anna. Our school was big enough that we had two teams that entered the competition. Thanks to David who interpreted the results pdf, last Saturday’s Botball tournament we got overall 22nd/27 teams. However, that score is determined by documentation and presentation as well as the actual tournament itself. So, if we only consider the tournament our two teams tied for 8th out of 27 teams! So, they did great :). Can’t wait for next year’s tournament!
I’m going to be a mentor again for Botball. This time I’m partnering with David, Kevin and Stephen and we are mentors for the middle school that David helped at last year. So, hopefully that means we will have more success than I had last year with Kramer middle school. This weekend is the intro/get everyone up to speed days and hopefully we can make use of the fact that the middle school participated last year to our advantage.
I talked to Professor Dominicani and about the fractal clustering idea (thinking of making it or pattern recognition class) and she had great suggestions. She recommended http://snap.stanford.edu/data/ that has a bunch of graph datasets (like social networks and the like). Since such things tend to be self similar it would seem like a perfect use-case for fractal clustering. She also suggested looking at sub-space clustering because it seemed similar to fractal clustering. http://www.cs.cmu.edu/~sguennem/ is the guy to look at for subspace clustering. Also, she said she has some students doing research in this area, so I can always ask them questions.
I also found http://pajek.imfm.si/doku.php?id=data:urls:index which has a ton of resources for network data sources.
http://vlado.fmf.uni-lj.si/pub/networks/data/ is another resource for network data.