Aditya Ghose - Academia.edu (original) (raw)

Papers by Aditya Ghose

Lecture Notes in Computer Science, 2012

Here we introduce a novel algorithm for continual optimisation of dynamic distributed constraint ... more Here we introduce a novel algorithm for continual optimisation of dynamic distributed constraint optimisation problems. By using techniques derived from argumentation for communication the algorithm does not need to use an ordering over the variables. The lack of a hierarchy allows the algorithm to efficiently solve dynamic problems, as well as be completely asynchronous, fault tolerant and anytime. However it prevents an ordered search, making the algorithm incomplete.

Lecture Notes in Computer Science, 2014

In this paper, we extend the Support Based Distributed Optimization (SBDO) algorithm to support p... more In this paper, we extend the Support Based Distributed Optimization (SBDO) algorithm to support problems which do not have a total pre-order over the set of solutions. This is the case in common real life problems that have multiple objective functions. In particular, decision support problems. These disparate objectives are not well supported by existing Distributed Constraint Optimization Problem (DCOP) techniques, which assume a single cost or utility function. As a result, existing Distributed COP techniques (with some recent exceptions) require that all agents subscribe to a common objective function and are therefore unsuitable for settings where agents have distinct, competing objectives. This makes existing constraint optimization technologies unsuitable for many decision support roles, where the decision maker wishes to observe the different trade-offs before making a decision.

Lecture Notes in Computer Science, 2012

Ensuring optimum use of scarce resources is one of the largest challenges facing health providers... more Ensuring optimum use of scarce resources is one of the largest challenges facing health providers today. However it is not easy to generate an optimised schedule, as the health system is unusually and highly dynamic. Scheduling systems must be extremely flexible ...

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 2011

The public health system is plagued by inefficient use of resources. Frequently, the results are ... more The public health system is plagued by inefficient use of resources. Frequently, the results are lengthy patient treatment waiting times. While many solutions for patient scheduling in health systems exist, few address the problem of coordination between independent autonomous departments. In this study, we describe the use of a distributed dynamic constraint optimisation algorithm (Support Based Distributed Optimisation) for the generation and optimisation of schedules across autonomous units. We model the problem of scheduling radiotherapy patients across several independent oncology units as a dynamic distributed constraint optimisation problem. Such an approach minimises the sharing of private information such as department operation details as well as patient privacy information while taking into consideration patient preferences as well as resource utilisation to find a pareto-optimal solution.

Computational Intelligence, 2004

Most existing formalizations treat belief change as a single-step process, and ignore several pro... more Most existing formalizations treat belief change as a single-step process, and ignore several problems that become important when a theory, or belief state, is revised over several steps. This paper identifies these problems, and argues for the need to retain all of the multiple possible outcomes of a belief change step, and for a framework in which the effects of a belief change step persist as long as is consistently possible. To demonstrate that such a formalization is indeed possible, we develop a framework, which uses the language of PJ-default logic (Delgrande and Jackson 1991) to represent a belief state, and which enables the effects of a belief change step to persist by propagating belief constraints. Belief change in this framework maps one belief state to another, where each belief state is a collection of theories given by the set of extensions of the PJ-default theory representing that belief state. Belief constraints do not need to be separately recorded; they are encoded as clearly identifiable components of a PJ-default theory. The framework meets the requirements for iterated belief change that we identify and satisfies most of the AGM postulates (Alchourrón, Gärdenfors, and Makinson 1985) as well.

In this paper we use i* which is a semi-formal modelling framework to model agent based applicati... more In this paper we use i* which is a semi-formal modelling framework to model agent based applications. We then describe how we execute these models into AgentSpeak(L) agents to form the essential components of a multi-agent system. We show that by making changes to the i* model we can generate different executable multi-agent systems. We also describe reverse mapping rules to see how changes to agents in the multi-agent system gets reflected in i* model. This co-evolution of two models offers a novel approach for configuring and prototyping agent based systems.

Agent–oriented conceptual modeling notations such as i* represents an interesting approach for mo... more Agent–oriented conceptual modeling notations such as i* represents an interesting approach for modeling early phase requirements which includes organizational con-texts, stakeholder intentions and rationale. On the other hand Use Case diagram is used for capturing ...

Agent–oriented conceptual modeling notations such as i* represents an interesting approach for mo... more Agent–oriented conceptual modeling notations such as i* represents an interesting approach for modeling early phase requirements which includes organizational con-texts, stakeholder intentions and rationale. On the other hand Use Case diagram is used for capturing ...

This work is to find a method for retrieving oncology documents relevant to clinical decision wit... more This work is to find a method for retrieving oncology documents relevant to clinical decision within the particular domain of cervix cancer, where traditional search by using keywords and Boolean logic cannot support
clinicians to find and assimilate all the literatures relevant to their research and
clinical decision. Thus, we propose an ontology-based text analysis to solve this
problem. Our work consists of two main contributions. First, we explore an
alternative solution to retrieve the relevant documents where the objective is to use content-based text classification (CBTC) as the key process for retrieving relevant documents. Second, we simplify and elaborate the process of selecting
the relevant document through similarity analysis. After testing by F-measure, the experimental results of text classifier and similarity analysis present the
accuracy at 87.20% and 92%, respectively. This demonstrates that our current proposal provides a preliminary indication of more effectiveness in retrieving relevant documents from PubMed.

This paper describes a framework that integrates case-based reasoning capabilities in a BDI agent... more This paper describes a framework that integrates case-based reasoning capabilities in a BDI agent architecture as well as its application to the design of Web information retrieval agents. The research proposed in this paper generates two key insights. First, it shows that the integration of case-based reasoning in a BDI agent architecture is a non-trivial exercise that suggests interesting ways of building BDI agents with learning capabilities. Second, it demonstrates the efficacy of the resulting framework by presenting the design of intelligent Web information retrieval agents that are effective in well-demarcated domains.

Due to changes in energy supply, and regulatory mechanism related to energy provisioning, organiz... more Due to changes in energy supply, and regulatory mechanism related to energy provisioning, organizations will need to tackle energy management issues. One way of doing so is to allocate resources to business processes taking
into account energy costs. However, energy costs are time-dependent, and the resource optimization problem needs to be redesigned. In this paper we formalize the energy-aware resource allocation problem, including time-dependent variable costs; describe how an auction mechanism can be used to allocate resources in a
way that optimizes costs; and present a case study.

Business processes represent the operational capabilities of an organization. In order to ensure ... more Business processes represent the operational capabilities of an organization. In order to ensure process
continuity, the effective management of risk becomes an area of key concern. In this paper we propose an
approach for supporting risk identification with the use of higher-level organizational models. We provide
some intuitive metrics for extracting measures of actor criticality, and vulnerability from organizational
models. This helps direct risk management to areas of critical importance within organization models.
Additionally, the information can be used to assess alternative organizational structures in domains where risk
mitigation is crucial. At the process level, these measures can be used to help direct improvements to the
robustness and failsafe capabilities of critical or vulnerable processes. We believe our novel approach, will
provide added benefits when used with other approaches to risk management during business process
management, that do not reference the greater organizational context during risk assessment.

Compliance issues impose significant management and reporting requirements upon organizations.We ... more Compliance issues impose significant management and reporting requirements upon organizations.We
present an approach to enhance business process modeling notations with the capability to detect and resolve
many broad compliance related issues. We provide a semantic characterization of a minimal revision strategy
that helps us obtain compliant process models from models that might be initially non-compliant, in a manner
that accommodates the structural and semantic dimensions of parsimoniously annotated process models. We
also provide a heuristic approach to compliance resolution using a notion of compliance patterns. This allows
us to partially automate compliance resolution, leading to reduced levels of analyst involvement and improved
decision support.

This paper addresses the problem of managing requirements evolution in situations where functiona... more This paper addresses the problem of managing requirements evolution in situations where functional and nonfunctional requirements interact and often contradict each other. It de nes a requirements representation scheme that captures the critical interplay between functional and non-functional requirements and makes explicit the trade-o between them. It then de nes a model of requirements evolution that involves mappings between such representations. This model turns out to have several useful properties, including guarantees of minimal change to speci cations as well support for requirements reuse.

This paper identifies ways in which traditional approaches to argumentation can be modified to me... more This paper identifies ways in which traditional approaches to
argumentation can be modified to meet the needs of practical
group decision support. A framework for outcome-driven decision
rationale management is proposed that permits a novel
conception of mixed-initiative argumentation. The framework
is evaluated in the context of group decision support
in medicine.

Operational risk is an important, complex, and difficult, criterion to consider during any form o... more Operational risk is an important, complex, and difficult, criterion to consider during any form of organizational decision making. In practice (1) complexity typically arises from: the use of a variety of risk related indicators; the use of multiple heterogeneous measurement scales; measurement uncertainty; varying levels of measurement precision; and, the widespread effect of each measurement; (2) difficulties arise due to the: time bound nature of the decision making process; and, the availability and interpretation of risk-related measurements. To help address these issues, we propose a conceptual framework to support and minimize the level of analyst involvement during the management of operational risk specified in organizational models. This is achieved by propagating/analyzing risk-related evaluations across descriptions of distributed, inter-dependant and mission critical work activities.

Business Process Management (BPM) has many anticipated benefits including accelerated process imp... more Business Process Management (BPM) has many anticipated
benefits including accelerated process improvement, at the operational level, with the use of highly configurable and adaptive “process aware” information systems [1] [2]. The facility for improved agility fosters the need for continual measurement and control of business processes to assess and manage their effective evolution, in-line with organizational objectives. This paper proposes the GoalBPM methodology for relating business process models (modeled using BPMN) to high-level stakeholder goals (modeled using KAOS). We propose informal (manual) techniques
(with likely future formalism) for establishing and verifying this relationship, even in dynamic environments where essential alterations to organizational goals and/or process constantly emerge.

Lecture Notes in Computer Science, 2012

Here we introduce a novel algorithm for continual optimisation of dynamic distributed constraint ... more Here we introduce a novel algorithm for continual optimisation of dynamic distributed constraint optimisation problems. By using techniques derived from argumentation for communication the algorithm does not need to use an ordering over the variables. The lack of a hierarchy allows the algorithm to efficiently solve dynamic problems, as well as be completely asynchronous, fault tolerant and anytime. However it prevents an ordered search, making the algorithm incomplete.

Lecture Notes in Computer Science, 2014

In this paper, we extend the Support Based Distributed Optimization (SBDO) algorithm to support p... more In this paper, we extend the Support Based Distributed Optimization (SBDO) algorithm to support problems which do not have a total pre-order over the set of solutions. This is the case in common real life problems that have multiple objective functions. In particular, decision support problems. These disparate objectives are not well supported by existing Distributed Constraint Optimization Problem (DCOP) techniques, which assume a single cost or utility function. As a result, existing Distributed COP techniques (with some recent exceptions) require that all agents subscribe to a common objective function and are therefore unsuitable for settings where agents have distinct, competing objectives. This makes existing constraint optimization technologies unsuitable for many decision support roles, where the decision maker wishes to observe the different trade-offs before making a decision.

Lecture Notes in Computer Science, 2012

Ensuring optimum use of scarce resources is one of the largest challenges facing health providers... more Ensuring optimum use of scarce resources is one of the largest challenges facing health providers today. However it is not easy to generate an optimised schedule, as the health system is unusually and highly dynamic. Scheduling systems must be extremely flexible ...

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 2011

The public health system is plagued by inefficient use of resources. Frequently, the results are ... more The public health system is plagued by inefficient use of resources. Frequently, the results are lengthy patient treatment waiting times. While many solutions for patient scheduling in health systems exist, few address the problem of coordination between independent autonomous departments. In this study, we describe the use of a distributed dynamic constraint optimisation algorithm (Support Based Distributed Optimisation) for the generation and optimisation of schedules across autonomous units. We model the problem of scheduling radiotherapy patients across several independent oncology units as a dynamic distributed constraint optimisation problem. Such an approach minimises the sharing of private information such as department operation details as well as patient privacy information while taking into consideration patient preferences as well as resource utilisation to find a pareto-optimal solution.

Computational Intelligence, 2004

Most existing formalizations treat belief change as a single-step process, and ignore several pro... more Most existing formalizations treat belief change as a single-step process, and ignore several problems that become important when a theory, or belief state, is revised over several steps. This paper identifies these problems, and argues for the need to retain all of the multiple possible outcomes of a belief change step, and for a framework in which the effects of a belief change step persist as long as is consistently possible. To demonstrate that such a formalization is indeed possible, we develop a framework, which uses the language of PJ-default logic (Delgrande and Jackson 1991) to represent a belief state, and which enables the effects of a belief change step to persist by propagating belief constraints. Belief change in this framework maps one belief state to another, where each belief state is a collection of theories given by the set of extensions of the PJ-default theory representing that belief state. Belief constraints do not need to be separately recorded; they are encoded as clearly identifiable components of a PJ-default theory. The framework meets the requirements for iterated belief change that we identify and satisfies most of the AGM postulates (Alchourrón, Gärdenfors, and Makinson 1985) as well.

In this paper we use i* which is a semi-formal modelling framework to model agent based applicati... more In this paper we use i* which is a semi-formal modelling framework to model agent based applications. We then describe how we execute these models into AgentSpeak(L) agents to form the essential components of a multi-agent system. We show that by making changes to the i* model we can generate different executable multi-agent systems. We also describe reverse mapping rules to see how changes to agents in the multi-agent system gets reflected in i* model. This co-evolution of two models offers a novel approach for configuring and prototyping agent based systems.

Agent–oriented conceptual modeling notations such as i* represents an interesting approach for mo... more Agent–oriented conceptual modeling notations such as i* represents an interesting approach for modeling early phase requirements which includes organizational con-texts, stakeholder intentions and rationale. On the other hand Use Case diagram is used for capturing ...

Agent–oriented conceptual modeling notations such as i* represents an interesting approach for mo... more Agent–oriented conceptual modeling notations such as i* represents an interesting approach for modeling early phase requirements which includes organizational con-texts, stakeholder intentions and rationale. On the other hand Use Case diagram is used for capturing ...

This work is to find a method for retrieving oncology documents relevant to clinical decision wit... more This work is to find a method for retrieving oncology documents relevant to clinical decision within the particular domain of cervix cancer, where traditional search by using keywords and Boolean logic cannot support
clinicians to find and assimilate all the literatures relevant to their research and
clinical decision. Thus, we propose an ontology-based text analysis to solve this
problem. Our work consists of two main contributions. First, we explore an
alternative solution to retrieve the relevant documents where the objective is to use content-based text classification (CBTC) as the key process for retrieving relevant documents. Second, we simplify and elaborate the process of selecting
the relevant document through similarity analysis. After testing by F-measure, the experimental results of text classifier and similarity analysis present the
accuracy at 87.20% and 92%, respectively. This demonstrates that our current proposal provides a preliminary indication of more effectiveness in retrieving relevant documents from PubMed.

This paper describes a framework that integrates case-based reasoning capabilities in a BDI agent... more This paper describes a framework that integrates case-based reasoning capabilities in a BDI agent architecture as well as its application to the design of Web information retrieval agents. The research proposed in this paper generates two key insights. First, it shows that the integration of case-based reasoning in a BDI agent architecture is a non-trivial exercise that suggests interesting ways of building BDI agents with learning capabilities. Second, it demonstrates the efficacy of the resulting framework by presenting the design of intelligent Web information retrieval agents that are effective in well-demarcated domains.

Due to changes in energy supply, and regulatory mechanism related to energy provisioning, organiz... more Due to changes in energy supply, and regulatory mechanism related to energy provisioning, organizations will need to tackle energy management issues. One way of doing so is to allocate resources to business processes taking
into account energy costs. However, energy costs are time-dependent, and the resource optimization problem needs to be redesigned. In this paper we formalize the energy-aware resource allocation problem, including time-dependent variable costs; describe how an auction mechanism can be used to allocate resources in a
way that optimizes costs; and present a case study.

Business processes represent the operational capabilities of an organization. In order to ensure ... more Business processes represent the operational capabilities of an organization. In order to ensure process
continuity, the effective management of risk becomes an area of key concern. In this paper we propose an
approach for supporting risk identification with the use of higher-level organizational models. We provide
some intuitive metrics for extracting measures of actor criticality, and vulnerability from organizational
models. This helps direct risk management to areas of critical importance within organization models.
Additionally, the information can be used to assess alternative organizational structures in domains where risk
mitigation is crucial. At the process level, these measures can be used to help direct improvements to the
robustness and failsafe capabilities of critical or vulnerable processes. We believe our novel approach, will
provide added benefits when used with other approaches to risk management during business process
management, that do not reference the greater organizational context during risk assessment.

Compliance issues impose significant management and reporting requirements upon organizations.We ... more Compliance issues impose significant management and reporting requirements upon organizations.We
present an approach to enhance business process modeling notations with the capability to detect and resolve
many broad compliance related issues. We provide a semantic characterization of a minimal revision strategy
that helps us obtain compliant process models from models that might be initially non-compliant, in a manner
that accommodates the structural and semantic dimensions of parsimoniously annotated process models. We
also provide a heuristic approach to compliance resolution using a notion of compliance patterns. This allows
us to partially automate compliance resolution, leading to reduced levels of analyst involvement and improved
decision support.

This paper addresses the problem of managing requirements evolution in situations where functiona... more This paper addresses the problem of managing requirements evolution in situations where functional and nonfunctional requirements interact and often contradict each other. It de nes a requirements representation scheme that captures the critical interplay between functional and non-functional requirements and makes explicit the trade-o between them. It then de nes a model of requirements evolution that involves mappings between such representations. This model turns out to have several useful properties, including guarantees of minimal change to speci cations as well support for requirements reuse.

This paper identifies ways in which traditional approaches to argumentation can be modified to me... more This paper identifies ways in which traditional approaches to
argumentation can be modified to meet the needs of practical
group decision support. A framework for outcome-driven decision
rationale management is proposed that permits a novel
conception of mixed-initiative argumentation. The framework
is evaluated in the context of group decision support
in medicine.

Operational risk is an important, complex, and difficult, criterion to consider during any form o... more Operational risk is an important, complex, and difficult, criterion to consider during any form of organizational decision making. In practice (1) complexity typically arises from: the use of a variety of risk related indicators; the use of multiple heterogeneous measurement scales; measurement uncertainty; varying levels of measurement precision; and, the widespread effect of each measurement; (2) difficulties arise due to the: time bound nature of the decision making process; and, the availability and interpretation of risk-related measurements. To help address these issues, we propose a conceptual framework to support and minimize the level of analyst involvement during the management of operational risk specified in organizational models. This is achieved by propagating/analyzing risk-related evaluations across descriptions of distributed, inter-dependant and mission critical work activities.

Business Process Management (BPM) has many anticipated benefits including accelerated process imp... more Business Process Management (BPM) has many anticipated
benefits including accelerated process improvement, at the operational level, with the use of highly configurable and adaptive “process aware” information systems [1] [2]. The facility for improved agility fosters the need for continual measurement and control of business processes to assess and manage their effective evolution, in-line with organizational objectives. This paper proposes the GoalBPM methodology for relating business process models (modeled using BPMN) to high-level stakeholder goals (modeled using KAOS). We propose informal (manual) techniques
(with likely future formalism) for establishing and verifying this relationship, even in dynamic environments where essential alterations to organizational goals and/or process constantly emerge.