Urjit Singh Bhatia | Georgia Institute of Technology (original) (raw)

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Papers by Urjit Singh Bhatia

Research paper thumbnail of Adaptive AI Players Strategy for FPS games

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Research paper thumbnail of Case Based Architect: CBArch

The paper introduces a first phase of development of a Case-Base Reasoning system intended to sup... more The paper introduces a first phase of development of a Case-Base Reasoning system intended to support early conceptual design of commercial buildings. At the current stage the research focuses on the integration of CaseBased Reasoning, Parametric Modeling (Building Information Modeling), and Ontology Reasoning. The goal is to take advantage of complementary capabilities of these technologies to support design. While CBR provides a framework to store and retrieve cases at an instance level, Parametric Modeling offers a framework for rule-based geometric adaptation and evaluation. The ontology is intended to provide a semantic representation, so that new design concepts can be created, classified and retained for further reuse. Instances can be organized under this conceptual umbrella, and new forms of design reasoning can be explored. Among them, it is foreseen new recommendation capabilities by offering unexpected cases to designers, improving the chances for innovative exploration within a wider scope of valid alternatives.

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Research paper thumbnail of Forensic Signature Verification

cc.gatech.edu

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Research paper thumbnail of Adaptive AI Players Strategy for FPS games

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Research paper thumbnail of Case Based Architect: CBArch

The paper introduces a first phase of development of a Case-Base Reasoning system intended to sup... more The paper introduces a first phase of development of a Case-Base Reasoning system intended to support early conceptual design of commercial buildings. At the current stage the research focuses on the integration of CaseBased Reasoning, Parametric Modeling (Building Information Modeling), and Ontology Reasoning. The goal is to take advantage of complementary capabilities of these technologies to support design. While CBR provides a framework to store and retrieve cases at an instance level, Parametric Modeling offers a framework for rule-based geometric adaptation and evaluation. The ontology is intended to provide a semantic representation, so that new design concepts can be created, classified and retained for further reuse. Instances can be organized under this conceptual umbrella, and new forms of design reasoning can be explored. Among them, it is foreseen new recommendation capabilities by offering unexpected cases to designers, improving the chances for innovative exploration within a wider scope of valid alternatives.

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Research paper thumbnail of Forensic Signature Verification

cc.gatech.edu

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