The following paper describes recent work on NED-2, an intelligent information system for ecosyst... more The following paper describes recent work on NED-2, an intelligent information system for ecosystem management currently in development by the USDA Forest Service. Using knowledge bases created by forestry experts and inference engines, NED-2 evaluates forest inventories according to a set of predefined goals. By integrating third-party simulation and visualization packages, NED-2 allows the user to plan, predict, and assess forest treatment scenarios. NED-2 is a blackboard system featuring agents implemented in PROLOG. Inventory, data calculation, and forest management plan creation modules are implemented in C++. The primary storage medium of NED-2 is a set of relational databases. The present paper focuses upon an issue of central importance to the project: the integration of PROLOG and relational databases to form the blackboard of NED-2.
In this paper, we combine deontic logic with Alternatingtime Temporal Logic (ATL) into a framewor... more In this paper, we combine deontic logic with Alternatingtime Temporal Logic (ATL) into a framework that makes it possible to model and reason about obligations and abilities of agents. The way both frameworks are combined is technically straightforward: we add deontic accessibility relations to ATL models (concurrent game structures), and deontic operators to the language of ATL (an additional operator UP is proposed for "unconditionally permitted" properties, similar to the "all I know" operator from epistemic logic). Our presentation is rather informal: we focus on examples of how obligations (interpreted as requirements) can be confronted with ways of satisfying them by actors of the game. Though some formal results are presented, the paper should not be regarded as a definite statement on how logics of obligation and strategic ability must be combined; instead, it is intended for stimulating discussion about such kinds of reasoning, and the models that can underpin it.
Artificial networks can be used to identify hydrogen nuclear magnetic resonance (1H-NMR) spectra ... more Artificial networks can be used to identify hydrogen nuclear magnetic resonance (1H-NMR) spectra of complex oligosaccharides. Feed-forward neural networks with back-propagation of errors can distinguish between spectra of oligosaccharides that differ by only one glycosyl residue in twenty. The artificial neural networks use features of the strongly overlapping region of the spectra (hump region) as well as features of the resolved regions of the spectra (structural reporter groups) to recognize spectra and efficiently recognized 1H-NMR spectra even when the spectra were perturbed by minor variations in their chemical shifts. Identification of spectra by neural network-based pattern recognition techniques required less than 0.1 second. It is anticipated that artificial neural networks can be used to identify the structures of any complex carbohydrate that has been previously characterized and for which a 1H-NMR spectrum is available.
Journal of Experimental & Theoretical Artificial Intelligence, 1990
Abstract The sceptical inheritance nets introduced in Horty et al.[Proceedings of AAAI-87 (1987):... more Abstract The sceptical inheritance nets introduced in Horty et al.[Proceedings of AAAI-87 (1987): 358-363] are translated into a version of Nute's defeasible logic. Moreover this translation is modular in the sense of Thomason and Horty [Non-Monotonic Reasoning. ...
Decision making for forest ecosystem management can include the use of a wide variety of modeling... more Decision making for forest ecosystem management can include the use of a wide variety of modeling tools. These tools include vegetation growth models, wildlife models, silvicultural models, GIS, and visualization tools. NED-2 is a robust, intelligent, goal-driven decision support system that integrates tools in each of these categories. NED-2 uses a blackboard architecture and a set of semiautonomous agents to manage these tools for the user. The blackboard integrates a Microsoft Access database and Prolog clauses, and the agents are implemented in Prolog. A graphical user interface written in Visual C++ provides powerful inventory analysis tools; dialogs for selecting timber, water, ecological, wildlife, and visual goals; and dialogs for defining treatments and building prescriptive management plans. Users can simulate management plans and perform goal analysis on different views of the management unit, where a view is determined by a management plan and a point in time. Prolog agents use growth and yield models to simulate management plans, perform goal analyses on userspecified views of the management unit, display results of plan simulation using GIS tools, and generate hypertext documents containing the results of such analysis. Individual agents use metaknowledge to set up and run external simulation models, to load rule-based models and perform inference, to set up and execute external GIS and visualization systems, and to generate hypertext reports as needed, relieving the user from performing all these tasks.
We propose development of an argument-based decision support system utilizing defeasible or nonmo... more We propose development of an argument-based decision support system utilizing defeasible or nonmonotonic reasoning. Defeasible logic graphs (d-graphs) represent the knowledge contained in a defeasible theory. A method for propagating labels through a d-graph is developed as a means for reasoning about the theory from which the d-graph is generated. This method is proven to be sound with respect to
We present a flexible, extensible method for integrating multiple tools into a single large decis... more We present a flexible, extensible method for integrating multiple tools into a single large decision support system (DSS) using a forest ecosystem management DSS (NED-2) as an example. In our approach, a rich ontology for the target domain is developed and implemented in the internal data model for the DSS. Semi-autonomous agents control external components and communicate using a blackboard. We illustrate how this multi-agent approach with its blackboard architecture supports the expansion of a DSS (in this case, NED-2) to incorporate new models and decision support tools as they become available. The exemplar NED-2 DSS developed using this method is a goal-driven DSS that integrates a sophisticated inventory system, treatment plan development, growth-and-yield models, wildlife models, fire risk models, knowledge based systems for goal satisfaction analysis, and a powerful report generation system.
NED-2 is a Windows-based system designed to improve project-level planning and decision making by... more NED-2 is a Windows-based system designed to improve project-level planning and decision making by providing useful and scientifically sound information to natural resource managers. Resources currently addressed include visual quality, ecology, forest health, timber, water, and wildlife. NED-2 expands on previous versions of NED applications by integrating treatment prescriptions, growth simulation, and alternative comparisons with evaluations of multiple resources across a management unit. The NED-2 system is adaptable for small private holdings, large public properties, or cooperative management across multiple ownerships. NED-2 implements a goal-driven decision process that ensures that all relevant goals are considered; the character and current condition of forestland are known; alternatives to manage the land are designed and tested; the future forest under each alternative is simulated; and the alternative selected achieves the owner's goals. NED-2 is designed to link with ଝ The computer programs described in this document are available with the understanding that the U.S. Department of Agriculture cannot assure their accuracy, completeness, reliability, or suitability for any purposes other than that reported. The use of trade, firm, or corporation names in this publication is for the information and convenience of the reader. Such use does not constitute an official endorsement or approval by the U.S. Department of Agriculture or the Forest Service of any product or service to the exclusion of others that may be suitable.
Decision making for forest ecosystem management can include the use of a wide variety of modeling... more Decision making for forest ecosystem management can include the use of a wide variety of modeling tools. These tools include vegetation growth models, wildlife models, silvicultural models, GIS, and visualization tools. NED-2 is a robust, intelligent, goal-driven decision support system that integrates tools in each of these categories. NED-2 uses a blackboard architecture and a set of semi-autonomous agents to manage these tools for the user. The blackboard integrates a Microsoft Access database and Prolog clauses, and the agents are implemented in Prolog. A graphical user interface written in Visual C++ provides powerful inventory analysis tools; dialogs for selecting timber, water, ecological, wildlife, and visual goals; and dialogs for defining treatments and building prescriptive management plans. Users can simulate management plans and perform goal analysis on different views of the management unit, where a view is determined by a management plan and a point in time. Prolog ag...
80 Methodological research at the ecoregional level-Review workshop Methodologies for Integrating... more 80 Methodological research at the ecoregional level-Review workshop Methodologies for Integrating Data Across Geographic Scales in a Data ... To date, census data and ad hoc household surveys have been primary mechanisms for inventorying a landscape resource base. ...
The following paper describes recent work on NED-2, an intelligent information system for ecosyst... more The following paper describes recent work on NED-2, an intelligent information system for ecosystem management currently in development by the USDA Forest Service. Using knowledge bases created by forestry experts and inference engines, NED-2 evaluates forest inventories according to a set of predefined goals. By integrating third-party simulation and visualization packages, NED-2 allows the user to plan, predict, and assess forest treatment scenarios. NED-2 is a blackboard system featuring agents implemented in PROLOG. Inventory, data calculation, and forest management plan creation modules are implemented in C++. The primary storage medium of NED-2 is a set of relational databases. The present paper focuses upon an issue of central importance to the project: the integration of PROLOG and relational databases to form the blackboard of NED-2.
In this paper, we combine deontic logic with Alternatingtime Temporal Logic (ATL) into a framewor... more In this paper, we combine deontic logic with Alternatingtime Temporal Logic (ATL) into a framework that makes it possible to model and reason about obligations and abilities of agents. The way both frameworks are combined is technically straightforward: we add deontic accessibility relations to ATL models (concurrent game structures), and deontic operators to the language of ATL (an additional operator UP is proposed for "unconditionally permitted" properties, similar to the "all I know" operator from epistemic logic). Our presentation is rather informal: we focus on examples of how obligations (interpreted as requirements) can be confronted with ways of satisfying them by actors of the game. Though some formal results are presented, the paper should not be regarded as a definite statement on how logics of obligation and strategic ability must be combined; instead, it is intended for stimulating discussion about such kinds of reasoning, and the models that can underpin it.
Artificial networks can be used to identify hydrogen nuclear magnetic resonance (1H-NMR) spectra ... more Artificial networks can be used to identify hydrogen nuclear magnetic resonance (1H-NMR) spectra of complex oligosaccharides. Feed-forward neural networks with back-propagation of errors can distinguish between spectra of oligosaccharides that differ by only one glycosyl residue in twenty. The artificial neural networks use features of the strongly overlapping region of the spectra (hump region) as well as features of the resolved regions of the spectra (structural reporter groups) to recognize spectra and efficiently recognized 1H-NMR spectra even when the spectra were perturbed by minor variations in their chemical shifts. Identification of spectra by neural network-based pattern recognition techniques required less than 0.1 second. It is anticipated that artificial neural networks can be used to identify the structures of any complex carbohydrate that has been previously characterized and for which a 1H-NMR spectrum is available.
Journal of Experimental & Theoretical Artificial Intelligence, 1990
Abstract The sceptical inheritance nets introduced in Horty et al.[Proceedings of AAAI-87 (1987):... more Abstract The sceptical inheritance nets introduced in Horty et al.[Proceedings of AAAI-87 (1987): 358-363] are translated into a version of Nute's defeasible logic. Moreover this translation is modular in the sense of Thomason and Horty [Non-Monotonic Reasoning. ...
Decision making for forest ecosystem management can include the use of a wide variety of modeling... more Decision making for forest ecosystem management can include the use of a wide variety of modeling tools. These tools include vegetation growth models, wildlife models, silvicultural models, GIS, and visualization tools. NED-2 is a robust, intelligent, goal-driven decision support system that integrates tools in each of these categories. NED-2 uses a blackboard architecture and a set of semiautonomous agents to manage these tools for the user. The blackboard integrates a Microsoft Access database and Prolog clauses, and the agents are implemented in Prolog. A graphical user interface written in Visual C++ provides powerful inventory analysis tools; dialogs for selecting timber, water, ecological, wildlife, and visual goals; and dialogs for defining treatments and building prescriptive management plans. Users can simulate management plans and perform goal analysis on different views of the management unit, where a view is determined by a management plan and a point in time. Prolog agents use growth and yield models to simulate management plans, perform goal analyses on userspecified views of the management unit, display results of plan simulation using GIS tools, and generate hypertext documents containing the results of such analysis. Individual agents use metaknowledge to set up and run external simulation models, to load rule-based models and perform inference, to set up and execute external GIS and visualization systems, and to generate hypertext reports as needed, relieving the user from performing all these tasks.
We propose development of an argument-based decision support system utilizing defeasible or nonmo... more We propose development of an argument-based decision support system utilizing defeasible or nonmonotonic reasoning. Defeasible logic graphs (d-graphs) represent the knowledge contained in a defeasible theory. A method for propagating labels through a d-graph is developed as a means for reasoning about the theory from which the d-graph is generated. This method is proven to be sound with respect to
We present a flexible, extensible method for integrating multiple tools into a single large decis... more We present a flexible, extensible method for integrating multiple tools into a single large decision support system (DSS) using a forest ecosystem management DSS (NED-2) as an example. In our approach, a rich ontology for the target domain is developed and implemented in the internal data model for the DSS. Semi-autonomous agents control external components and communicate using a blackboard. We illustrate how this multi-agent approach with its blackboard architecture supports the expansion of a DSS (in this case, NED-2) to incorporate new models and decision support tools as they become available. The exemplar NED-2 DSS developed using this method is a goal-driven DSS that integrates a sophisticated inventory system, treatment plan development, growth-and-yield models, wildlife models, fire risk models, knowledge based systems for goal satisfaction analysis, and a powerful report generation system.
NED-2 is a Windows-based system designed to improve project-level planning and decision making by... more NED-2 is a Windows-based system designed to improve project-level planning and decision making by providing useful and scientifically sound information to natural resource managers. Resources currently addressed include visual quality, ecology, forest health, timber, water, and wildlife. NED-2 expands on previous versions of NED applications by integrating treatment prescriptions, growth simulation, and alternative comparisons with evaluations of multiple resources across a management unit. The NED-2 system is adaptable for small private holdings, large public properties, or cooperative management across multiple ownerships. NED-2 implements a goal-driven decision process that ensures that all relevant goals are considered; the character and current condition of forestland are known; alternatives to manage the land are designed and tested; the future forest under each alternative is simulated; and the alternative selected achieves the owner's goals. NED-2 is designed to link with ଝ The computer programs described in this document are available with the understanding that the U.S. Department of Agriculture cannot assure their accuracy, completeness, reliability, or suitability for any purposes other than that reported. The use of trade, firm, or corporation names in this publication is for the information and convenience of the reader. Such use does not constitute an official endorsement or approval by the U.S. Department of Agriculture or the Forest Service of any product or service to the exclusion of others that may be suitable.
Decision making for forest ecosystem management can include the use of a wide variety of modeling... more Decision making for forest ecosystem management can include the use of a wide variety of modeling tools. These tools include vegetation growth models, wildlife models, silvicultural models, GIS, and visualization tools. NED-2 is a robust, intelligent, goal-driven decision support system that integrates tools in each of these categories. NED-2 uses a blackboard architecture and a set of semi-autonomous agents to manage these tools for the user. The blackboard integrates a Microsoft Access database and Prolog clauses, and the agents are implemented in Prolog. A graphical user interface written in Visual C++ provides powerful inventory analysis tools; dialogs for selecting timber, water, ecological, wildlife, and visual goals; and dialogs for defining treatments and building prescriptive management plans. Users can simulate management plans and perform goal analysis on different views of the management unit, where a view is determined by a management plan and a point in time. Prolog ag...
80 Methodological research at the ecoregional level-Review workshop Methodologies for Integrating... more 80 Methodological research at the ecoregional level-Review workshop Methodologies for Integrating Data Across Geographic Scales in a Data ... To date, census data and ad hoc household surveys have been primary mechanisms for inventorying a landscape resource base. ...
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Papers by Donald Nute