Game theory models decision makers' behaviors in strategic situations. Since the structures of games are different, behavior and preferences of the players are different in various types of game. This paper reviews various situations of games. Here, characteristics of some common games are discussed and compared. Specifically, we focus on a group of games called symmetric games including Prison...

Dynamic scripting is a reinforcement learning algorithm designed specifically to learn appropriate tactics for an agent in a modern computer game, such as Neverwinter Nights. This reinforcement learning algorithm has previously been extended to support the automatic construction of new abstract states to improve its context sensitivity and integrated with a graphical behavior modeling architect...

Planning is an important cognitive process. We are constantly involved in planning even when executing seemingly simple tasks such as driving to school. The ability to plan becomes essential in unfamiliar environments where we cannot rely on previously learned action sequences, but instead have to generate novel solutions by considering consequences of action choices on the fly. Planning in rea...

We describe a 3-layer architecture for an automated Real-Time Strategy game player. In these kinds of games, opponent players create and manage large armies of units to defeat one another requiring strategic thinking. Players give commands asynchronously, requiring rapid thinking and reaction. Our 3-layer architecture builds on current automated players for these kinds of games, which focuses o...

Although massive multiplayer online games have established popularity, real-time strategy (RTS) has not been considered a good candidate for this model because of the limited number of players supported, large number of game entities and strong consistency requirements. To deal with this situation, concepts such as continuous consistency and location-awareness have proven useful in order to con...

This thesis presents and analyses the problem of small scale combat (SSC) in real time strategy (RTS) computer games. An RTS game is a war simulator where several opposing factions battle in a virtual world. The problem of SSC appears when soldiers, called units, of opposing factions meet in this virtual world. In commercial RTS games SSC situations are handled by applying simple rules to each ...

Developing computer-controlled groups to engage in combat, control the use of limited resources, and create units and buildings in Real-Time Strategy(RTS) Games is a novel application in game AI. However, a controlled and closed console commercial game environment pose challenges to researchers interested in observing player activities, constructing player strategy models, and developing practi...

There has been significant recent interest in game theoretic approaches to security, with much of the recent research focused on utilizing the leader-follower Stackelberg game model; for example, these games are at the heart of major applications such as the ARMOR program deployed for security at the LAX airport since 2007 and the IRIS program in use by the US Federal Air Marshals (FAMS). The f...

Automatic strategy synthesis for a given control objective can be used to generate correct-by-construction controllers of reactive systems. The existing symbolic approach for continuous timed games is a computationally hard task and current tools like UPPAAL TiGa often scale poorly with the model complexity. We suggest an explicit approach for strategy synthesis in the discrete-time setting and...

Real-time Strategy (RTS) games are complex domains which are a significant challenge to both human and artificial intelligence (AI). For that reason, and although many AI approaches have been proposed for the RTS game AI problem, the AI of all commercial RTS games is scripted and offers a very static behavior subject to exploits. In this paper, we will focus on a case-based reasoning (CBR) appr...