Bonny Banerjee
University of Memphis
Diagrammatic reasoningHuman–computer interactionMachine learningData miningBenchmark (computing)Artificial intelligenceSet (psychology)Domain (software engineering)Pattern recognitionConstraint satisfaction problemGestureInferenceSpeech recognitionComputer visionMathematicsComputer scienceProcess (engineering)Constraint satisfactionArtificial neural networkFeature extractionFeature learningCluster analysisTheoretical computer science
61Publications
11H-index
270Citations
Publications 59
Newest
Jan 1, 2013 in AAAI (National Conference on Artificial Intelligence)
#1Bonny Banerjee (U of M: University of Memphis)H-Index: 11
2 Citations
#1B. Chandrasekaran (OSU: Ohio State University)H-Index: 52
#2Bonny Banerjee (OSU: Ohio State University)H-Index: 11
Last. Omkar Lele (OSU: Ohio State University)H-Index: 4
view all 4 authors...
Diagrams are a form of spatial representation that supports reasoning and problem solving. Even when diagrams are external, not to mention when there are no external representations, problem solving often calls for internal representations, that is, representations in cognition, of diagrammatic elements and internal perceptions on them. General cognitive architectures—Soar and ACT-R, to name the most prominent—do not have representations and operations to support diagrammatic reasoning. In this ...
10 CitationsSource
#1Bonny Banerjee (OSU: Ohio State University)H-Index: 11
#2B. Chandrasekaran (OSU: Ohio State University)H-Index: 52
Diagrammatic reasoning (DR) is pervasive in human problem solving as a powerful adjunct to symbolic reasoning based on language-like representations. The research reported in this paper is a contribution to building a general purpose DR system as an extension to a soar-like problem solving architecture. The work is in a framework in which DR is modeled as a process where subtasks are solved, as appropriate, either by inference from symbolic representations or by interaction with a diagram, i.e.,...
9 CitationsSource
#1Bonny Banerjee (OSU: Ohio State University)H-Index: 11
#2B. Chandrasekaran (OSU: Ohio State University)H-Index: 52
Diagrammatic reasoning (DR) requires perceiving information from a diagram and modifying/creating objects in a diagram according to problem solving needs. The perceptions and actions in most DR systems are hand-coded for the specific application. The absence of a general framework for executing perceptions/actions poses as a major hindrance to using them opportunistically. Our goal is to develop a framework for executing a wide variety of specified perceptions and actions across tasks/domains wi...
9 CitationsSource
#1Bonny BanerjeeH-Index: 11
#2B. ChandrasekaranH-Index: 52
4 CitationsSource
#1Bonny Banerjee (OSU: Ohio State University)H-Index: 11
#2B. Chandrasekaran (OSU: Ohio State University)H-Index: 52
Spatial problems (SP) are inevitable in reasoning with diagrams. In this paper, we investigate general representations and computational strategies for a SP-solver such that it can accept problems from a human in a high-level language and output the solution without human intervention. We propose a language in which a variety of domain- independent 2D SPs can be specified in terms of constraints. The constraints are specified in first-order logic over the real domain using a vocabulary of object...
1 CitationsSource
The phenomenon of self-organization has been of special interest to the neural network community throughout the last couple of decades. In this paper, we study a variant of the self-organizing map (SOM) that models the phenomenon of self-organization of the particles forming a string when the string is tightened from one or both of its ends. The proposed variant, called the string tightening self-organizing neural network (STON), can be used to solve certain practical problems, such as computati...
5 CitationsSource
#1B. Chandrasekaran (OSU: Ohio State University)H-Index: 52
#2Bonny Banerjee (OSU: Ohio State University)H-Index: 11
Diagrammatic reasoning (DR) is pervasive in human problem solving as a powerful adjunct to symbolic reasoning based on language-like representations. However, Artificial Intelligence is overwhelmingly based on symbolic representations, with proportionately scant attention to diagrams. This dissertation is a contribution to building artificial agents that can create and use diagrams as part of their problem solving. The work is in a framework in which DR is modeled as a process in which subtasks ...
8 Citations
#1Bonny Banerjee (OSU: Ohio State University)H-Index: 11
#2B. Chandrasekaran (OSU: Ohio State University)H-Index: 52
A diagrammatic problem-solver requires a library of visual routines (VRs) and action routines (ARs) – the VRs are used to obtain information of specified types from the diagram and ARs to modify the diagram in specified ways. The VRs/ARs required are unbounded – a new domain may call for new perceptions and actions. We report on progress on our research in building an automated VR/AR synthesis system that would take as input the definition of a new routine in terms of existing routines in the li...
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3 CitationsSource