In these days I am reviewing CIG papers. At the moment, I am not active in academia, but I enjoy being around in the community. Even if only with this “simple” tasks.

This, however, makes me think about the state of scientific work in academia. At least in the computer science field. Something bothered me during my Ph.D. and I am sure it is related to that. (Note: I am talking about what I know, that is, the computer science and AI community) In general, researchers are evaluated on the number of publications. The number of publications is a proxy variable for measuring “quality”. Unfortunately, researchers know that and started to game the system. They try to publish more and to do that they need to lower the “quality” of their work. Because the medium used to communicate your work is a plain PFD file, the obvious way to cut work is to cut the implementation part.

You know I worked a lot with pathfinding. In academia, the MovingAI benchmark created by the MovingAI Lab of the University of Denver is a must for benchmarking pathfinding algorithms. It includes synthetic maps and maps from commercial videogames.

Parsing the benchmark data, the maps, creating the map data structure and more, is one of the most boring thing I needed to do for testing my algorithms. For this reason, I think a common library for working with the maps specifications it is a must.

This article has been originally published on Gamasutra.

In the last article we introduced a basic approach for Inventory-Aware Pathfinding (IAP), a pathfinding algorithm capable of interacting with obstacles and not just avoiding them. If you have not read it, I encourage you to go back and read it to understand the basic challenges and the main ideas behind the proposed solution.

For instance, we can have a pathfinding algorithm that can solve small plans and “puzzles” involving reasoning like “before passing this door, I need to get that key”. This is definitely planning territory. However, if we focus on a small subset of the problem, we may squeeze the algorithm into the pathfinding search itself.

There is a common question in academia for people working on videogames: “Is there a consensus on how to cite videogames in academic papers?”. Obviously not, there is no consensus and probably never will. However, I will try to show you a solution to this problem that I enjoyed a lot in the last months. It is clear, it is customizable and it is the most formal way I’ve found to do that.

As you probably know, last week I was at the DiGRA-FDG conference in Dundee, Scotland. The conference ended last week, but I have the urge to add something to a really interesting presentation I’ve attended during the first day at the workshop on Procedural Contents Generation.

Before FDG, I was reading a small book on how the Chinese language has evolved during the centuries. It is extremely interesting. Especially if we look at the clear and wonderful evolution from pictures on paleolithic wood artifacts to the modern Mandarin Language. This triggered in me the idea to explore the literature on teleological algorithms for the procedural generation of languages (if you don’t know, the teleological algorithms in PCG are the ones that try to generate a “thing” by simulating the physical and evolutionary processes through which the “thing” is generated in the Real World™).

I’m back! During the last week, I had a beautiful experience as a volunteer at the Nucl.ai 2016 conference, one of the nicest Game AI related conferences in Europe.

I like this conference. It has a very informal atmosphere and both speakers and attendees are incredibly friendly and very willing in giving advice. You can go there like a complete no-one (for instance, like me) and you can speak and have a beer with Lead AI programmer in Triple-A games, in top notch industries like Google, Blizzard or Epic as if they are your friends.

Everybody know what pathfinding is. I don’t think I have to explain to a game developers audience why pathfinding is so important in games. If something in your game is moving not in a straight line, then you are using some kind of pathfinding.

What is less evident is that pathfinding is the only place in which “searching” is generally accepted. Except for GOAP and other planning-based techniques, the big part of the NPC’s decision-making techniques are reactive-based.

This is not a bad thing. Reactive techniques are an amazing design tool. However, this raises a question. Why is this? Mainly because of computational limits - full-fledged planning still requires an impractical amount of time - but also because of design unpredictability. The output of planning decision-making techniques is hard to control and the final behavior of the agent could be counterintuitive for the designers and, at the end, for the players.

Why can pathfinding play a role in this? Because it is possible to embed in it a minimal, specialized, subset of planning, especially if these planning instances require spatial reasoning. A common example is solving a pathfinding problem in which areas of the map are blocked by doors that can be open by switches or keys sparse around on the map. How can we solve this kind of problems?

8th September 2016 Update: I uploaded these slides on SlideShare. You can see them here. Hi guys! In the last month I’ve prepared a presentation on Procedural Contents Generation history and techniques in commercial videogames. I did this presentation for a Game Jam some time ago and for a series of meetings in our university. I think it is a nice summary of the main elements of PCG in commercial games, so I think it is worth to share this presentation with you!

Hi everyone! Sorry for the long absence but my days are really full of commitments and terrible news. It is still not over, but but I really need write about something before is too late. :) During the last 3th-7th October, the tenth conference on Artificial Intelligence for Interactive Digital Entertainment (AIIDE) was held in Raleigh (North Carolina, USA). It was a very interesting conference on AI and games stuff and I am really happy to have joined such amazing things. I mean, this is something that I could proudly say to the 10 years old me and make him happy and unbelieving. I could look the younger me in the eyes and say “In the future you’ll participate in a conference about artificial intelligence and videogames with some of the most beautiful mind in that field!”. Wow. However, unfortunately I received too many commitments and bad news from Italy to be able to freely enjoy this conference and to be fully concentrated. I’m really sorry of this.

Hi everyone! I’m back. In the last week I was in Prague to attend to the 21th European Conerence on Artificial Intelligence (a.k.a. ECAI2014). This was my first real academic conference since I started my Ph.D. in the last November.  As I said before, conferences are amazing events where I get stressed like never before but, at the end, I come back home super-excited and full of inspirational ideas. Moreover, in these type of events you are surrounded by amazing people that do what you do. Meeting and talking with them is always insightful and amazing. So, first of all, thanks to all the nice people I met during this conference.