Publishing venues for works in the field of multi-agent systems

Because publish or perish is still a fact of life in 2014 for all aspiring researchers, here are some publishing venues for papers in the field of multi-agent systems.


For conferences, there is the International Conference on Autonomous Agents and Multiagent Systems (AAMAS), sponsored by the International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), and for journals there is the Autonomous Agents and Multi-Agent Systems, which is an ISI journal.


The Multi-agent Systems and Optimization Research Group in the Research Institute IRTES, at the Université de Technologie de Belfort-Montbéliard also have an excellence page that lists all the journals and conferences that accept works in the field of multi-agent systems.


Poppler font rendering bug and a workaround

So lately I’ve been plagued with a bug where fi and fl ligatures are not displayed in Okular. Needless to say, this makes reading textbooks, especially mathematics textbooks with all those words like “define” and “definition”, supremely annoying.

After finally having some free time, I started googling around and finally found the cause. It’s a bug with poppler.

Fortunately, there is a workaround that solves the problem. Hopefully this bug will get a properly fix soon, but for now this will do.

Markov Chains Learning Resources

Since it looks like that there is a very high chance that I’ll have to use Markov Chains in my research, I’ve been searching and reading up on the subject.

The following are the links & articles on Markov Chains that I’ve found useful.

  • Markov Chains, a visual explanation is a great introduction to Markov Chains. Like its name implies, the blog post contained a lot of great interactive graphs that offer immense help in understanding what Markov Chains are and how they work. Also, the Hacker News and Reddit threads on the post also contain a lot of interesting discussions, my favorite of which is the following short and concise explanation of what is a Markov Chain: “Markov chain = probabilistic (finite) state machine”.
  • Analysis of Chutes and Ladders and Candyland are a great pair of articles that show how to use Markov Chains to analyze complex games of chance.
  • The Model Thinking course on Coursera has a nice set of video lectures on the subject.
  • This Stack Overflow thread describes how Markov Chains and (finite) state machines are related (in short, Markov Chains can be represented by (finite) state machines).