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The 2010 Mario AI Championship, the successor to the 2009 Mario AI Competition, will run in association with several major international conferences focusing on computational intelligence and games. The competition will consist of three tracks: Gameplay, Learning and Level Generation, with partly overlapping organizers.
Real-time strategy games (RTS) are an active area of research as well as a popular branch of industrial game production, with high commercial interest. Although player satisfaction is the ultimate goal also for these games, they are usually too complex to come up with human-level AI that is not cheating. In consequence, for RTS games it is as desirable to play well as it is to make the game interesting...
After decades of developing and dreaming in the field of Artificial Life, fundamental breakthroughs in computational complexity and laboratory chemical simulation hold forth the promise that virtual worlds may become the proving grounds for an authentic artificial proto-biosystem. Early self-organization and complex phenomena within game spaces and virtual worlds suggest what form this profound new...
Board games are often taken as examples to teach decision-making algorithms in artificial intelligence (AI). These algorithms are generally presented with a strong focus on winning the game. Unfortunately, a few important aspects, such as the gaming experience of human players, are often missing from the equation. This paper presents a simple board game we use in an introductory course in AI to initiate...
We study the problem of a mobile agent trying to cross an area patrolled by a mobile adversary. The transiting agent aims to choose its route so as to minimize the probability of hostile encounter; the patroller agent, controlling one or more patrol units, aims at the opposite. We model the problem as a two-player zero-sum game (termed transit game) and search for an optimum route selection strategy...
Social agents have the ability of communicating and forming groups with each other. Group members in games typically share the same role. In dynamic environments with the presence of obstacles and barriers separating members from each other presents a situation where a member separated from the rest of the group, while still a member of that group, should not have the same role or updates of the rest...
Genetic operations that consider effective building blocks are proposed for using genetic algorithms to solve Sudoku puzzles. A stronger local search function is also proposed. Evaluation of the proposed techniques using commercial Sudoku puzzle sets and three puzzles ranked as super difficult compared with previously reported examples show that the rate of optimum solutions can be greatly improved...
We present the application of genetic programming (GP) to the zero-sum, deterministic, full-knowledge board game of Lose Checkers. Our system implements strongly typed GP trees, explicitly defined introns, local mutations, and multi-tree individuals. Explicitly defined introns in the genome allow for information selected out of the population to be kept as a reservoir for possible future use. Multi-tree...
A MasterMind player must find out a secret combination (set by another player) by playing others of the same kind and using the hints obtained as a response (which reveal how close the played combination is to the secret one) to produce new combinations. Despite having been researched for a number of years, there are still many open issues: finding a strategy to select the next combination to play...
In RTS-style games it is important to be able to predict the movements of the opponent's forces to have the best chance of performing appropriate counter-moves. Resorting to using perfect global state information is generally considered to be `cheating' by the player, so to perform such predictions scouts (or observers) must be used to gather information. This means being in the right place at the...
Fingerprinting is a mathematical technique that generates a representation-independent functional signature for a game-playing agent, allowing for systematic and automated analysis of strategies. In this study, the global structure and mutational connectivity network for a depth-3 lookup table with prior move history playing Prisoner's Dilemma is investigated at different choices of the time-scale...
Learning has always been one of the core mechanics in computer games. Players learn specific battle mechanics, control schemes, and much more, which enables them to progress further through the game and experience pleasure. Previous studies on learning often focused on the learning of predictors (cues) for reward and their motivational properties, but fail to address the impact on pleasure. For example,...
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