52,661 research outputs found
Generative Design in Minecraft: Chronicle Challenge
© 2016 ACC 2019We introduce the Chronicle Challenge as an optional addition to the Settlement Generation Challenge in Minecraft. One of the foci of the overall competition is adaptive procedural content generation (PCG), an arguably under-explored problem in computational creativity. In the base challenge, participants must generate new settlements that respond to and ideally interact with existing content in the world, such as the landscape or climate. The goal is to understand the underlying creative process, and to design better PCG systems. The Chronicle Challenge in particular focuses on the generation of a narrative based on the history of a generated settlement, expressed in natural language. We discuss the unique features of the Chronicle Challenge in comparison to other competitions, clarify the characteristics of a chronicle eligible for submission and describe the evaluation criteria. We furthermore draw on simulation-based approaches in computational storytelling as examples to how this challenge could be approached.Peer reviewe
Rational Trust Modeling
Trust models are widely used in various computer science disciplines. The
main purpose of a trust model is to continuously measure trustworthiness of a
set of entities based on their behaviors. In this article, the novel notion of
"rational trust modeling" is introduced by bridging trust management and game
theory. Note that trust models/reputation systems have been used in game theory
(e.g., repeated games) for a long time, however, game theory has not been
utilized in the process of trust model construction; this is where the novelty
of our approach comes from. In our proposed setting, the designer of a trust
model assumes that the players who intend to utilize the model are
rational/selfish, i.e., they decide to become trustworthy or untrustworthy
based on the utility that they can gain. In other words, the players are
incentivized (or penalized) by the model itself to act properly. The problem of
trust management can be then approached by game theoretical analyses and
solution concepts such as Nash equilibrium. Although rationality might be
built-in in some existing trust models, we intend to formalize the notion of
rational trust modeling from the designer's perspective. This approach will
result in two fascinating outcomes. First of all, the designer of a trust model
can incentivise trustworthiness in the first place by incorporating proper
parameters into the trust function, which can be later utilized among selfish
players in strategic trust-based interactions (e.g., e-commerce scenarios).
Furthermore, using a rational trust model, we can prevent many well-known
attacks on trust models. These two prominent properties also help us to predict
behavior of the players in subsequent steps by game theoretical analyses
Games and Brain-Computer Interfaces: The State of the Art
BCI gaming is a very young field; most games are proof-of-concepts. Work that compares BCIs in a game environments with traditional BCIs indicates no negative effects, or even a positive effect of the rich visual environments on the performance. The low transfer-rate of current games poses a problem for control of a game. This is often solved by changing the goal of the game. Multi-modal input with BCI forms an promising solution, as does assigning more meaningful functionality to BCI control
Deep learning for video game playing
In this article, we review recent Deep Learning advances in the context of
how they have been applied to play different types of video games such as
first-person shooters, arcade games, and real-time strategy games. We analyze
the unique requirements that different game genres pose to a deep learning
system and highlight important open challenges in the context of applying these
machine learning methods to video games, such as general game playing, dealing
with extremely large decision spaces and sparse rewards
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