Fernando De Mesentier Silva

Fernando De Mesentier Silva
New York University | NYU · Department of Computer Science

Doctor of Philosophy

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23
Publications
38,260
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445
Citations

Publications

Publications (23)
Preprint
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Many games are reliant on creating new and engaging content constantly to maintain the interest of their player-base. One such example are puzzle games, in such it is common to have a recurrent need to create new puzzles. Creating new puzzles requires guaranteeing that they are solvable and interesting to players, both of which require significant...
Article
Full-text available
Recently, there have been several high-profile achievements of agents learning to play games against humans and beat them. In this paper, we study the problem of training intelligent agents in service of game development. Unlike the agents built to “beat the game”, our agents aim to produce human-like behavior to help with game evaluation and balan...
Article
Full-text available
Since the inception of artificial intelligence, games have benchmarked algorithmic advances. Recent success in classic board games such as Chess and Go have left space for video games that pose related yet different sets of challenges. With this shifted focus, the set of AI problems associated with video games has expanded from simply playing these...
Conference Paper
Full-text available
Videogame designers use tips and tricks and tools of the trade to design levels. Some of these tips are based on their gut feeling and others have been known in the game industry for the last 30 years. In this work, we discuss six of common level design patterns present in 2D videogames. The patterns under discussion are the product of an explorato...
Article
Full-text available
Balancing an ever growing strategic game of high complexity, such as Hearthstone is a complex task. The target of making strategies diverse and customizable results in a delicate intricate system. Tuning over 2000 cards to generate the desired outcome without disrupting the existing environment becomes a laborious challenge. In this paper, we discu...
Conference Paper
Full-text available
Balancing an ever growing strategic game of high complexity, such as Hearthstone is a complex task. The target of making strategies diverse and customizable results in a delicate intricate system. Tuning over 2000 cards to generate the desired outcome without disrupting the existing environment becomes a laborious challenge. In this paper, we discu...
Preprint
Full-text available
Matching tile games are an extremely popular game genre. Arguably the most popular iteration, Match-3 games, are simple to understand puzzle games, making them great benchmarks for research. In this paper, we propose developing different procedural personas for Match-3 games in order to approximate different human playstyles to create an automated...
Preprint
Full-text available
Games have benchmarked AI methods since the inception of the field, with classic board games such as Chess and Go recently leaving room for video games with related yet different sets of challenges. The set of AI problems associated with video games has in recent decades expanded from simply playing games to win, to playing games in particular styl...
Conference Paper
Quality diversity (QD) algorithms such as MAP-Elites have emerged as a powerful alternative to traditional single-objective optimization methods. They were initially applied to evolutionary robotics problems such as locomotion and maze navigation, but have yet to see widespread application. We argue that these algorithms are perfectly suited to the...
Preprint
Balancing an ever growing strategic game of high complexity, such as Hearthstone is a complex task. The target of making strategies diverse and customizable results in a delicate intricate system. Tuning over 2000 cards to generate the desired outcome without disrupting the existing environment becomes a laborious challenge. In this paper, we discu...
Preprint
Full-text available
Quality diversity (QD) algorithms such as MAP-Elites have emerged as a powerful alternative to traditional single-objective optimization methods. They were initially applied to evolutionary robotics problems such as locomotion and maze navigation, but have yet to see widespread application. We argue that these algorithms are perfectly suited to the...
Preprint
Full-text available
Recently, there have been several high-profile achievements of agents learning to play games against humans and beat them. In this paper, we study the problem of training intelligent agents in service of game development. Unlike the agents built to “beat the game”, our agents aim to produce human-like behavior to help with game evaluation and balan...
Preprint
Full-text available
The process of playtesting a game is subjective, expensive and incomplete. In this paper, we present a playtesting approach that explores the game space with automated agents and collects data to answer questions posed by the designers. Rather than have agents interacting with an actual game client, this approach recreates the bare bone mechanics o...
Article
The process of play testing a game is subjective, expensive and incomplete. In this paper, we present a play-testing approach that explores the game space with automated agents and collects data to answer questions posed by the designers. Rather than have agents interacting with an actual game client, this approach recreates the bare bone mechanics...
Conference Paper
Full-text available
A significant issue in game balancing is understanding the game itself. For simple games end-to-end optimization approaches can help explore the game's design space, but for more complex games it is necessary to isolate and explore its parts. Hearthstone, Blizzard's popular two-player turn-taking adversarial card game, has two distinct game-playing...
Conference Paper
Full-text available
We present a search-based approach to generating boards and decks of cards for the game Ticket to Ride. Our evolutionary algorithm searches for boards that allow for a well-shaped game arc, and for decks that promote an equal distribution of desirability for cities. We show examples of two boards generated by our algorithm and compare our results t...
Conference Paper
Full-text available
We introduce several deck of cards and dice models that can be used to represent stochastic outcomes in tabletop games. We analyze these using a toy game introduced as a Micro Combat game. By simulating the outcome of the game with these different models we can analyze them in terms of their salience, disparity, fairness and obfuscation. We expect...
Conference Paper
Full-text available
Beginner heuristics for a game are simple rules that allow for effective playing. A chain of beginner heuristics of length N is the list of N rules that play the game best. Finding beginner heuristics is useful both for teaching a novice to play the game well and for understanding the dynamics of the game. We present and compare methods for finding...
Conference Paper
Full-text available
Ticket to Ride is a popular contemporary board game for two to four players, featuring a number of expansions with additional maps and tweaks to the core game mechanics. In this paper, four different game-playing agents that embody different playing styles are defined and used to analyze Ticket to Ride. Different playing styles are shown to be effe...
Article
Full-text available
Buses are the primary means of public transportation in the city of Rio de Janeiro, carrying around 100 million passengers every month. Recently, real-time GPS coordinates of all operating public buses has been made publicly available - roughly 1 million GPS entries each captured each day. In an initial study, we observed that a substantial number...

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