Collecting dance videos, preserving and promoting them after enriching the collected data has been significant actions in preserving Intangible culture heritage in South-East Asia. Whereas techniques for the conceptual modeling of the expressive semantics of dance videos are very complex, they are crucial to exploit effectively the video semantics. This paper proposes an ontology web-based dance video annotation system for representing the semantics of dance videos at different granularity levels. Especially, the system incorporates both syntactic and semantic features of pre-built dance ontology system in order to not only use the available semantic web system but also to create unity for users when annotating videos to minimize conflicts.
This paper deals with a nondeterministic dice-based game: Heckmeck am Bratwurmeck (Pickomino). This game is based on dice rolling and on the stop or roll principle. To decide between going on rolling or stopping a player has to estimate his chances of improving his score and of losing. To do so he takes into account the previous dice rolls and evaluates the risk for the next ones.Since the standard methods for nondeterministic games cannot be used directly, we conceived original algorithms for Pickomino presented in this paper. The first ones are based on hard rules and not really satisfactory as their playing level proved to be weak. We propose then an algorithm using a Monte-Carlo method to evaluate probabilities of dice rolls and the accessibility of resources. By using this tactical computing in different ways the programs can play according to the stage of the game (beginning or end). Finally, we present experimental results comparing all the proposed algorithms. Over 7,500,000 matches opposed the different AIs and the winner of this contest turns out to be a strong opponent for human players.
Modeling intention is essential to explain decisions made by agents. In this work, we propose a model of intention in epistemic games, represented in dynamic epistemic logic. Given a property and a sequence of actions already performed by a player in such a game, we propose a method able to determine whether the player had the intention to obtain the property. An illustration of the method is given using a simplified version of the collaborative game Hanabi.
Rational agents' decisions are driven by their intentions, in the sense that agents execute actions that most probably lead to situations where their intentions are achieved. Using that insight, this paper proposes a method for 'intention checking': let a description of a game, a state and the action executed by the agent at that state be given, the method checks whether the agent acted with the intention to reach a situation where some proposition 'p' is true. We use a logic with epistemic and temporal operators to reason about games and extend it with an intention operator 'IX'. Formulas of the form 'IX(p)' are defined to be true in the situations where the intention check method verifies that the agent acts with the intention to achieve 'p' in the next state of the game. We show that this operator satisfies the principles of Bratman's Asymmetry Thesis, and we also compare it to other theories of intention.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.