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Conference proceeding
Situation assessment for plan retrieval in real-time strategy games
ADVANCES IN CASE-BASED REASONING, PROCEEDINGS, v 5239, pp 355-369
01 Jan 2008
Abstract
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 [8,3]. 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 concept of a situation and explain a situation assessment algorithm which improves plan retrieval for CBP. We have applied situation assessment to our previous CBP system, Darmok [11], in the domain of real-time strategy games. During Darmok's execution using situation assessment, the high-level representation of the game state i.e. situation is predicted using a decision tree based Situation-Classification model. Situation predicted is further used for the selection of relevant knowledge intensive features, which are derived from the basic representation of the game state, to compute the similarity of cases with the current problem. The feature selection performed here is knowledge based and improves the performance of similarity measurements during plan retrieval. The instantiation of the situation assessment algorithm to Darmok gave us promising results for plan retrieval within the real-time constraints.
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Details
- Title
- Situation assessment for plan retrieval in real-time strategy games
- Creators
- Kinshuk Mishra - Georgia Institute of TechnologySantiago Ontanon - Georgia Institute of TechnologyAshwin Ram - Georgia Institute of Technology
- Contributors
- K D Althoff (Editor)R Bergmann (Editor)M Minor (Editor)A Hanft (Editor)
- Publication Details
- ADVANCES IN CASE-BASED REASONING, PROCEEDINGS, v 5239, pp 355-369
- Series
- Lecture Notes in Artificial Intelligence
- Publisher
- Springer Nature
- Number of pages
- 15
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Computer Science
- Web of Science ID
- WOS:000259463400024
- Scopus ID
- 2-s2.0-52149084376
- Other Identifier
- 991021869113204721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Computer Science, Software Engineering