gilgi.org (Posts about Dota 2)

Dota 2 friend network visualization

gilgi — Wed, 14 Aug 2019 04:00:00 GMT

What better way is there to enjoy games than with friends? Of course, some friends have better synergies than others. What if there was a way to quantify those synergies and draw a group of friends as a graph, with high-synergy friends placed close together and low-synergy friends placed further apart?

In this post, we'll use the OpenDota API, multidimensional scaling (MDS), and networkx to visualize a network of friends playing Dota 2 together.

Visualizing trajectories of Dota Auto Chess games using LDA and TSNE

gilgi — Sat, 18 May 2019 04:00:00 GMT

The Dota 2 custom map "Dota Auto Chess" is taking the gaming world by storm. Auto Chess is almost like a card game in which players attempt to improve their hand round after round while their "chesses" (cards) battle the other players in the game automatically. In this post, we'll explore the potential of latent Dirichlet allocation to model strategies (specific combinations of cards that are often played together) as "topics". We will then try to visualize the evolution of Auto Chess "hands" over the course of individual games in terms of their topics using t-SNE. These kinds of visualizations might help us learn how to more effectively evolve our strategies.

Creating Dota 2 hero embeddings with Word2vec

gilgi — Sun, 27 May 2018 04:00:00 GMT

One of the coolest results in natural language processing is the success of word embedding models like Word2vec. These models are able to extract rich semantic information from words using surprisingly simple models like CBOW or skip-gram. What if we could use these generic modelling strategies to learn embeddings for something completely different - say, Dota 2 heroes.

In this post, we'll use the OpenDota API to collect data from professional Dota 2 matches and use Keras to train a Word2vec-like model for hero embeddings.