User-generated content is everywhere: photos, videos, news, blogs, art, music, and every other type of digital media on the Social Web. Games are no exception. From strategy games to immersive virtual worlds, game players are increasingly engaged in creating and sharing nearly all aspects of the gaming experience: maps, quests, artifacts, avatars, clothing, even games [...]
Posts Tagged ‘real-time cbr’
20 Jan
On-Line Case-Based Planning
Some domains, such as real-time strategy (RTS) games, pose several challenges to traditional planning and machine learning techniques. In this paper, we present a novel on-line case-based planning architecture that addresses some of these problems. Our architecture addresses issues of plan acquisition, on-line plan execution, interleaved planning and execution and on-line plan adaptation. We also [...]
2 Sep
Real-Time Plan Adaptation for Case-Based Planning in Real-Time Strategy Games
Case-based planning (CBP) is based on reusing past successful plans for solving new problems. CBP is particularly useful in environments where the large amount of time required to traverse extensive search spaces makes traditional planning techniques unsuitable. In particular, in real-time domains, past plans need to be retrieved and adapted in real time and efficient [...]
2 Sep
Situation Assessment for Plan Retrieval in Real-Time Strategy Games
Case-Based Planning (CBP) is an effective technique for solving planning problems that has the potential to reduce the computational complexity of the generative planning approaches. However, the success of plan execution using CBP depends highly on the selection of a correct plan; especially when the case-base of plans is extensive.
In this paper we introduce the [...]
16 Jul
On-Line Case-Based Plan Adaptation for Real-Time Strategy Games
Traditional artificial intelligence techniques do not perform well in applications such as real-time strategy games because of the extensive search spaces which need to be explored. In addition, this exploration must be carried out on-line during performance time; it cannot be precomputed. We have developed on-line case-based planning techniques that are effective in such domains. [...]
16 Aug
Case-Based Planning and Execution for Real-Time Strategy Games
Artificial Intelligence techniques have been successfully applied to several computer games. However in some kinds of computer games, like real-time strategy (RTS) games, traditional artificial intelligence techniques fail to play at a human level because of the vast search spaces that they entail. In this paper we present a real-time case based planning and execution [...]
11 Jan
Transfer Learning in Real-Time Strategy Games Using Hybrid CBR/RL
The goal of transfer learning is to use the knowledge acquired in a set of source tasks to improve performance in a related but previously unseen target task. In this paper, we present a multi-layered architecture named CAse-Based Reinforcement Learner (CARL). It uses a novel combination of Case-Based Reasoning (CBR) and Reinforcement Learning (RL) to [...]
15 May
Case-Based Reasoning for Gas Turbine Diagnostics
General Electric used case-based reasoning for gas turbine diagnostics at their monitoring and diagnostics center in Atlanta, GA. This application had requirements that included accuracy, maintainability, modularity, parameterization, robustness, and integration of the system into an existing infrastructure. The CBR system has a modular “plug and play” architecture to facilitate experimentation and optimization. It was [...]
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