Resources, Entities, Actions. A generalized design pattern for RTS games and its language extension in Casanova
نویسندگان
چکیده
Real-time strategy (RTS) games are popular and many different games exist. Despite the existence of basic similarities among different games, the engines of these games are often built ad hoc, and code re-use among di erent titles is minimal. We abstract one such similarity into a new design pattern, and implement the design pattern and its language abstraction in the Casanova programming language. The language abstraction is purely declarative; its semantics are shown using SQL. The design pattern allows a developer to create RTS games without having to write large amounts of boilerplate code. Developers can focus on the important bits of the game, such as AI, gameplay, etc. Run time e ciency is also improved. In our case studies we nd speedups of 6 to 25 times. This paper describes the design pattern, its language extension in Casanova, and provides evidence of the e ciency gains possible in terms of lines of code and run time e ciency.
منابع مشابه
Resource Entity Action: A Generalized Design Pattern for RTS Games
In Real-Time Strategy (RTS) games, players develop an army in real time, then attempt to take out one or more opponents. Despite the existence of basic similarities among the many di erent RTS games, engines of these games are often built ad hoc, and code re-use among di erent titles is minimal. We created a design pattern called Resource Entity Action (REA) that abstracts the basic interaction...
متن کاملWriting Real-Time .Net Games in Casanova
In this paper we show the Casanova language (and its accompanying design pattern, Rule-Script-Draw) in action by building a series of games with it. In particular we discuss how Casanova is suitable for making games regardless of their genre: the Game of Life, a shooter game, an adventure game and a strategy game. We also discuss the difference between Casanova and existing frameworks.
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 کاملUtilizing Generalized Learning Automata for Finding Optimal Policies in MMDPs
Multi agent Markov decision processes (MMDPs), as the generalization of Markov decision processes to the multi agent case, have long been used for modeling multi agent system and are used as a suitable framework for Multi agent Reinforcement Learning. In this paper, a generalized learning automata based algorithm for finding optimal policies in MMDP is proposed. In the proposed algorithm, MMDP ...
متن کاملConcurrent Action Execution with Shared Fluents
Concurrent action execution is important for plan-length minimization. However, action specifications are often limited to avoid conflicts arising from precondition/effect interactions. PDDL — the planning domain definition language — for example, implements the “no moving targets” rule, which means that no two actions can simultaneously make use of a value if one of the two is updating the val...
متن کامل