Opponent Modeling and Spatial Similarity to Retrieve and Reuse Superior Plays
نویسندگان
چکیده
Plays are sequences of actions to be undertaken by a collection of agents, or teammates. The success of a play depends on a number of factors including, perhaps most importantly, the opponent’s play. In this paper, we present an approach for online opponent modeling and illustrate how it can be used to improve offensive performance in the Rush 2008 football simulator. In football, team behaviors have an observable spatio-temporal structure, defined by the relative physical positions of team members over time. We demonstrate that this structure can be exploited to recognize football plays at a very early stage. Using the recognized defensive play, knowledge about expected outcomes, and spatial similarity between offensive plays, we retrieve an offensive play from the case base. This play is then (partially) reused to improve an in-progress offensive play. We call this process a play switch. Empirical results indicate that spatial similarity is central to play retrieval, and that substituting only a subset of the current play yields greater improvement over a full play substitution.
منابع مشابه
Developing a BIM-based Spatial Ontology for Semantic Querying of 3D Property Information
With the growing dominance of complex and multi-level urban structures, current cadastral systems, which are often developed based on 2D representations, are not capable of providing unambiguous spatial information about urban properties. Therefore, the concept of 3D cadastre is proposed to support 3D digital representation of land and properties and facilitate the communication of legal owners...
متن کاملRobust Opponent Modeling in Real-Time Strategy Games using Bayesian Networks
Opponent modeling is a key challenge in Real-Time Strategy (RTS) games as the environment is adversarial in these games, and the player cannot predict the future actions of her opponent. Additionally, the environment is partially observable due to the fog of war. In this paper, we propose an opponent model which is robust to the observation noise existing due to the fog of war. In order to cope...
متن کاملImproving Offensive Performance Through Opponent Modeling
Although in theory opponent modeling can be useful in any adversarial domain, in practice it is both difficult to do accurately and to use effectively to improve game play. In this paper, we present an approach for online opponent modeling and illustrate how it can be used to improve offensive performance in the Rush 2008 football game. In football, team behaviors have an observable spatio-temp...
متن کاملRetrieving and reusing qualitative cases: An application in humanoid-robot soccer
This paper proposes a new Case-Based Reasoning (CBR) approach, named Q-CBR, that uses a Qualitative Spatial Reasoning theory to model, retrieve and reuse cases by means of spatial relations. Qualitative relations between objects, represented in terms of the EOPRA formalism, are stored as qualitative cases that are applied in the definition of new retrieval and reuse algorithms. The retrieval al...
متن کاملInvestigating Embedded Question Reuse in Question Answering
The investigation presented in this paper is a novel method in question answering (QA) that enables a QA system to gain performance through reuse of information in the answer to one question to answer another related question. Our analysis shows that a pair of question in a general open domain QA can have embedding relation through their mentions of noun phrase expressions. We present methods f...
متن کامل