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Children with Autistic Spectrum Disorder (ASD)have marked impairments in social interaction. Imitation is abasic social interaction behavior, and mimicking as an element of imitation can be a diagnostic marker for autism and thus a skill that can be targeted by behavioral training. In a comparative study between children with and without autism (n=20), we designed a test that aims to find differences...
Equilibrium selection in networks is difficult. Players have to both choose their contacts and their actions. In this paper, we formally and experimentally analyze three variants of the game varying the strategy set of the players. We formally show, that limiting the strategy set can both increase and decrease the number of sub game perfect equilibria in the game. Human participants playing these...
This research is to design a digital game, Emotion Labyrinth, to help users to learn to rationalize emotions in the gaming process. It is a 3D simulated game through which the users learn to turn negative emotions into positive emotions. At the end of the game, the system would generate a narrative story describing the users emotional changes happened in the process so that the users can revisit his/her...
The strong revenue generating engines of mobile social games have caught attention of both researchers and the industry. The analysis of revenue-generating engines has identified the characteristics of service engineering in the era of social media and services. One such finding is that mobile social game design creates different types of satisfaction with a single service, which is unique in social...
Often the AI techniques for decision making used in commercial games are predictable and unadaptive. Arguably, this causes a lack of realism for the players. We believe that emotions are a vital part in the creation of interesting and believable non-player characters for games. In this paper, we present an extension to behavior trees that incorporates emotions into the decision making. Specifically,...
The video games industry is one of the fastest-growing industries in the world, bolstered by sophisticated technology in gaming consoles and modern trends such as mobile and social gaming. The goal of most video games is to entertain the gamer and in most games this stems from the interaction between the gamer and the non-player characters (NPCs): it is no longer sufficient for a game to be visually...
We present a controller for the Physical Travelling Salesman Problem (PTSP), a path planning and steering problem in a simulated continuous real-time domain. Our approach is hierarchical, using domain-specific algorithms and heuristics to plan a coarse-grained route and Monte Carlo Tree Search (MCTS) to plan and steer along fine-grained paths. The MCTS component uses macro-actions to decrease the...
This paper describes the early stages of an experiment investigating the role of the computer as a creative collaborator in the game design process. We introduce the Shibumi set, a closed game system so simple that its rule space can be completely defined, yet deep enough to allow interesting games to emerge. Constraining the search space to such a closed system has computational benefits, but had...
In this work, personality profiles are used to develop parameterized bot behaviors. While the personality profile structure was originally designed as a descriptive tool for human behavior, as used here it is a generative tool, allowing a plurality of different behaviors to result from a single rule set. This paper describes our use of the Five-Factor Model of personality to develop a bot that plays...
We describe a generative Bayesian model of tactical attacks in strategy games, which can be used both to predict attacks and to take tactical decisions. This model is designed to easily integrate and merge information from other (probabilistic) estimations and heuristics. In particular, it handles uncertainty in enemy units' positions as well as their probable tech tree. We claim that learning, being...
We present the huddle, a concept for extending games in which the player is responsible for a group of game characters. The huddle combines several AI methods to allow the player to create a cooperative strategy for his characters to solve a scenario of the game and it takes away from the player the need to frantically jump around in controlling his characters to employ the strategy idea he has. The...
This work compares the learning of linear evaluation functions using preference learning versus least squares temporal difference learning, LSTD(λ), from samples of game trajectories. The game trajectories are taken from human competitions held by the French Othello Federation1. The raw board positions are used to create a linear evaluation function to illustrate the key difference between the two...
Over the past decades, video games have become increasingly popular and complex. Virtual worlds have gone a long way since the first arcades and so have the artificial intelligence (AI) techniques used to control agents in these growing environments. Tasks such as world exploration, constrained pathfinding or team tactics and coordination just to name a few are now default requirements for contemporary...
We present the work on our integrated AI system SCAIL, which is capable of playing a full round of the Real-Time Strategy game Starcraft. Our system makes use of modern AI techniques such as particle filtering, on-line machine learning, drive-based motivation systems and artificial emotions, used to find novel structure in the dynamic playing environment, which is exploited by both high and low-level...
Interactive training is a technique that allows humans to guide a learning algorithm. This technique is well suited to training first person shooter bots as it allows game designers to iterate a range of behaviors in real-time. This paper investigates an initial attempt at allowing users to interact with the learning process of a reinforcement learning algorithm to create first person shooter bot...
This paper presents the use of design grammars to evolve playable 2D platform levels through grammatical evolution (GE). Representing levels using design grammars allows simple encoding of important level design constraints, and allows remarkably compact descriptions of large spaces of levels. The expressive range of the GE-based level generator is analyzed and quantitatively compared to other feature-based...
We present the application of genetic programming to the zero-sum, deterministic, full-knowledge board game of Reversi. Expanding on our previous work on evolving boardstate evaluation functions, we now evolve the search algorithm as well, by allowing evolved programs control of game-tree pruning. We use strongly typed genetic programming, explicitly defined introns, and a selective directional crossover...
Cooperation in nature is a complex topic and its study has left scientists with many open questions. Over the past two decades research has been undertaken into how cooperation works in an evolutionary context and how we can emulate it for social analysis. Numerous computer models have been developed and analyzed, with many models formulated as spatial or network games. These games use various update...
During the last years the well-known Ms. Pac Man video game has been — and still is — an interesting test bed for the research on various concepts from the broad area of Artificial Intelligence (AI). Among these concepts is the use of Genetic Programming (GP) to control the game from a human player's perspective. Several GP-based approaches have been examined so far, where traditionally they define...
We investigate the practical effectiveness of a theoretically sound algorithm for dynamic difficulty adjustment in computer games: Firstly, we show how the partially ordered set master (Posm) algorithm [11] can be incorporated in board games, taking checkers and Chinese chess as examples. Secondly, we describe an empirical study of (i) Posm on checkers against synthetic opponents of varying strength,...
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