Typescript. / Thesis (Ph. D.)--University of Hawaii at Manoa, 1985. / Bibliography: leaves [372]-384. / Photocopy. / Microfilm. / x, 384 leaves, bound ill. 29 cm

The graph model for conflict resolution (GMCR) provides a convenient and effective means to model and analyze a strategic conflict. Standard practice is to carry out a stability analysis of a graph model, and then to follow up with a post-stability analysis, two critical components of which are status quo analysis and coalition analysis. In stability analysis, an equilibrium is a state that is stable for all decision makers (DMs) under appropriate stability definitions or solution concepts. Status quo analysis aims to determine whether a particular equilibrium is reachable from a status quo (or an initial state) and, if so, how to reach it. A coalition is any subset of a set of DMs. The coalition stability analysis within the graph model is focused on the status quo states that are equilibria and assesses whether states that are stable from individual viewpoints may be unstable for coalitions. Stability analysis began within a simple preference structure which includes a relative preference relationship and an indifference relation. Subsequently, preference uncertainty and strength of preference were introduced into GMCR but not formally integrated. In this thesis, two new preference frameworks, hybrid preference and multiple-level preference, and an integrated algebraic approach are developed for GMCR. Hybrid preference extends existing preference structures to combine preference uncertainty and strength of preference into GMCR. A multiple-level preference framework expands GMCR to handle a more general and flexible structure than any existing system representing strength of preference. An integrated algebraic approach reveals a link among traditional stability analysis, status quo analysis, and coalition stability analysis by using matrix representation of the graph model for conflict resolution. To integrate the three existing preference structures into a hybrid system, a new preference framework is proposed for graph models using a quadruple relation to express strong or mild preference of one state or scenario over another, equal preference, and an uncertain preference. In addition, a multiple-level preference framework is introduced into the graph model methodology to handle multiple-level preference information, which lies between relative and cardinal preferences in information content. The existing structure with strength of preference takes into account that if a state is stable, it may be either strongly stable or weakly stable in the context of three levels of strength. However, the three-level structure is limited in its ability to depict the intensity of relative preference. In this research, four basic solution concepts consisting of Nash stability, general metarationality, symmetric metarationality, and sequential stability, are defined at each level of preference for the graph model with the extended multiple-level preference. The development of the two new preference frameworks expands the realm of applicability of the graph model and provides new insights into strategic conflicts so that more practical and complicated problems can be analyzed at greater depth. Because a graph model of a conflict consists of several interrelated graphs, it is natural to ask whether well-known results of Algebraic Graph Theory can help analyze a graph model. Analysis of a graph model involves searching paths in a graph but an important restriction of a graph model is that no DM can move twice in succession along any path. (If a DM can move consecutively, then this DM's graph is effectively transitive. Prohibiting consecutive moves thus allows for graph models with intransitive graphs, which are sometimes useful in practice.) Therefore, a graph model must be treated as an edge-weighted, colored multidigraph in which each arc represents a legal unilateral move and distinct colors refer to different DMs. The weight of an arc could represent some preference attribute. Tracing the evolution of a conflict in status quo analysis is converted to searching all colored paths from a status quo to a particular outcome in an edge-weighted, colored multidigraph. Generally, an adjacency matrix can determine a simple digraph and all state-by-state paths between any two vertices. However, if a graph model contains multiple arcs between the same two states controlled by different DMs, the adjacency matrix would be unable to track all aspects of conflict evolution from the status quo. To bridge the gap, a conversion function using the matrix representation is designed to transform the original problem of searching edge-weighted, colored paths in a colored multidigraph to a standard problem of finding paths in a simple digraph with no color constraints. As well, several unexpected and useful links among status quo analysis, stability analysis, and coalition analysis are revealed using the conversion function. The key input of stability analysis is the reachable list of a DM, or a coalition, by a legal move (in one step) or by a legal sequence of unilateral moves, from a status quo in 2-DM or $n$-DM ($n > 2$) models. A weighted reachability matrix for a DM or a coalition along weighted colored paths is designed to construct the reachable list using the aforementioned conversion function. The weight of each edge in a graph model is defined according to the preference structure, for example, simple preference, preference with uncertainty, or preference with strength. Furthermore, a graph model and the four basic graph model solution concepts are formulated explicitly using the weighted reachability matrix for the three preference structures. The explicit matrix representation for conflict resolution (MRCR) that facilitates stability calculations in both 2-DM and $n$-DM ($n > 2$) models for three existing preference structures. In addition, the weighted reachability matrix by a coalition is used to produce matrix representation of coalition stabilities in multiple-decision-maker conflicts for the three preference frameworks. Previously, solution concepts in the graph model were traditionally defined logically, in terms of the underlying graphs and preference relations. When status quo analysis algorithms were developed, this line of thinking was retained and pseudo-codes were developed following a similar logical structure. However, as was noted in the development of the decision support system (DSS) GMCR II, the nature of logical representations makes coding difficult. The DSS GMCR II, is available for basic stability analysis and status quo analysis within simple preference, but is difficult to modify or adapt to other preference structures. Compared with existing graphical or logical representation, matrix representation for conflict resolution (MRCR) is more effective and convenient for computer implementation and for adapting to new analysis techniques. Moreover, due to an inherent link between stability analysis and post-stability analysis presented, the proposed algebraic approach establishes an integrated paradigm of matrix representation for the graph model for conflict resolution.

The graph model for conflict resolution (GMCR) provides a convenient and effective means to model and analyze a strategic conflict. Standard practice is to carry out a stability analysis of a graph model, and then to follow up with a post-stability analysis, two critical components of which are status quo analysis and coalition analysis. In stability analysis, an equilibrium is a state that is stable for all decision makers (DMs) under appropriate stability definitions or solution concepts. Status quo analysis aims to determine whether a particular equilibrium is reachable from a status quo (or an initial state) and, if so, how to reach it. A coalition is any subset of a set of DMs. The coalition stability analysis within the graph model is focused on the status quo states that are equilibria and assesses whether states that are stable from individual viewpoints may be unstable for coalitions. Stability analysis began within a simple preference structure which includes a relative preference relationship and an indifference relation. Subsequently, preference uncertainty and strength of preference were introduced into GMCR but not formally integrated. In this thesis, two new preference frameworks, hybrid preference and multiple-level preference, and an integrated algebraic approach are developed for GMCR. Hybrid preference extends existing preference structures to combine preference uncertainty and strength of preference into GMCR. A multiple-level preference framework expands GMCR to handle a more general and flexible structure than any existing system representing strength of preference. An integrated algebraic approach reveals a link among traditional stability analysis, status quo analysis, and coalition stability analysis by using matrix representation of the graph model for conflict resolution. To integrate the three existing preference structures into a hybrid system, a new preference framework is proposed for graph models using a quadruple relation to express strong or mild preference of one state or scenario over another, equal preference, and an uncertain preference. In addition, a multiple-level preference framework is introduced into the graph model methodology to handle multiple-level preference information, which lies between relative and cardinal preferences in information content. The existing structure with strength of preference takes into account that if a state is stable, it may be either strongly stable or weakly stable in the context of three levels of strength. However, the three-level structure is limited in its ability to depict the intensity of relative preference. In this research, four basic solution concepts consisting of Nash stability, general metarationality, symmetric metarationality, and sequential stability, are defined at each level of preference for the graph model with the extended multiple-level preference. The development of the two new preference frameworks expands the realm of applicability of the graph model and provides new insights into strategic conflicts so that more practical and complicated problems can be analyzed at greater depth. Because a graph model of a conflict consists of several interrelated graphs, it is natural to ask whether well-known results of Algebraic Graph Theory can help analyze a graph model. Analysis of a graph model involves searching paths in a graph but an important restriction of a graph model is that no DM can move twice in succession along any path. (If a DM can move consecutively, then this DM's graph is effectively transitive. Prohibiting consecutive moves thus allows for graph models with intransitive graphs, which are sometimes useful in practice.) Therefore, a graph model must be treated as an edge-weighted, colored multidigraph in which each arc represents a legal unilateral move and distinct colors refer to different DMs. The weight of an arc could represent some preference attribute. Tracing the evolution of a conflict in status quo analysis is converted to searching all colored paths from a status quo to a particular outcome in an edge-weighted, colored multidigraph. Generally, an adjacency matrix can determine a simple digraph and all state-by-state paths between any two vertices. However, if a graph model contains multiple arcs between the same two states controlled by different DMs, the adjacency matrix would be unable to track all aspects of conflict evolution from the status quo. To bridge the gap, a conversion function using the matrix representation is designed to transform the original problem of searching edge-weighted, colored paths in a colored multidigraph to a standard problem of finding paths in a simple digraph with no color constraints. As well, several unexpected and useful links among status quo analysis, stability analysis, and coalition analysis are revealed using the conversion function. The key input of stability analysis is the reachable list of a DM, or a coalition, by a legal move (in one step) or by a legal sequence of unilateral moves, from a status quo in 2-DM or $n$-DM ($n > 2$) models. A weighted reachability matrix for a DM or a coalition along weighted colored paths is designed to construct the reachable list using the aforementioned conversion function. The weight of each edge in a graph model is defined according to the preference structure, for example, simple preference, preference with uncertainty, or preference with strength. Furthermore, a graph model and the four basic graph model solution concepts are formulated explicitly using the weighted reachability matrix for the three preference structures. The explicit matrix representation for conflict resolution (MRCR) that facilitates stability calculations in both 2-DM and $n$-DM ($n > 2$) models for three existing preference structures. In addition, the weighted reachability matrix by a coalition is used to produce matrix representation of coalition stabilities in multiple-decision-maker conflicts for the three preference frameworks. Previously, solution concepts in the graph model were traditionally defined logically, in terms of the underlying graphs and preference relations. When status quo analysis algorithms were developed, this line of thinking was retained and pseudo-codes were developed following a similar logical structure. However, as was noted in the development of the decision support system (DSS) GMCR II, the nature of logical representations makes coding difficult. The DSS GMCR II, is available for basic stability analysis and status quo analysis within simple preference, but is difficult to modify or adapt to other preference structures. Compared with existing graphical or logical representation, matrix representation for conflict resolution (MRCR) is more effective and convenient for computer implementation and for adapting to new analysis techniques. Moreover, due to an inherent link between stability analysis and post-stability analysis presented, the proposed algebraic approach establishes an integrated paradigm of matrix representation for the graph model for conflict resolution.

Yes

Transaction programs are comprised of read and write operations issued against the database. In a shared database system, one transaction program conflicts with another if it reads or writes data that another transaction program has written. This thesis presents a semi-automatic technique for pairwise static conflict analysis of embedded transaction programs. The analysis predicts whether a given pair of programs will conflict when executed against the database. There are several potential applications of this technique, the most obvious being transaction concurrency control in systems where it is not necessary to support arbitrary, dynamic queries and updates. By analyzing transactions in such systems before the transactions are run, it is possible to reduce or eliminate the need for locking or other dynamic concurrency control schemes.

Transaction programs are comprised of read and write operations issued against the database. In a shared database system, one transaction program conflicts with another if it reads or writes data that another transaction program has written. This thesis presents a semi-automatic technique for pairwise static conflict analysis of embedded transaction programs. The analysis predicts whether a given pair of programs will conflict when executed against the database. There are several potential applications of this technique, the most obvious being transaction concurrency control in systems where it is not necessary to support arbitrary, dynamic queries and updates. By analyzing transactions in such systems before the transactions are run, it is possible to reduce or eliminate the need for locking or other dynamic concurrency control schemes.

An enhanced attitudes methodology within the framework of the Graph Model for Conflict Resolution (GMCR) is developed and applied to a range of environmental disputes, including a sustainable development conflict, an international climate change negotiation and a selection of brownfield conflicts over a proposed transfer of ownership. GMCR and the attitudes framework are first defined and then applied to a possible Sino-American climate negotiation over reductions in greenhouse gas emissions. A formal relationship between the attitudes framework and relative preferences is defined and associated mathematical theorems, which relate the moves and solution concepts used in both types of analysis, are proven. Significant extensions of the attitudes methodology are devised in the thesis. The first, dominating attitudes is a methodology by which the importance of a decision maker’s (DM’s) attitudes can be used to evaluate the strength of a given state stability. The second, COalitions and ATtitudes (COAT), is an expansion of both the attitudes and coalitions frameworks which allows one to analyze the impact of attitudes within a collaborative decision making setting. Finally, the matrix form of attitudes, is a mathematical methodology which allows complicated solution concepts to be executed using matrix operations and thus make attitudes more adaptable to a coding environment. When applied to environmental management conflicts, these innovative expansions of the attitudes framework illustrate the importance of cooperation and diplomacy in environmental conflict resolution.

An enhanced attitudes methodology within the framework of the Graph Model for Conflict Resolution (GMCR) is developed and applied to a range of environmental disputes, including a sustainable development conflict, an international climate change negotiation and a selection of brownfield conflicts over a proposed transfer of ownership. GMCR and the attitudes framework are first defined and then applied to a possible Sino-American climate negotiation over reductions in greenhouse gas emissions. A formal relationship between the attitudes framework and relative preferences is defined and associated mathematical theorems, which relate the moves and solution concepts used in both types of analysis, are proven. Significant extensions of the attitudes methodology are devised in the thesis. The first, dominating attitudes is a methodology by which the importance of a decision maker’s (DM’s) attitudes can be used to evaluate the strength of a given state stability. The second, COalitions and ATtitudes (COAT), is an expansion of both the attitudes and coalitions frameworks which allows one to analyze the impact of attitudes within a collaborative decision making setting. Finally, the matrix form of attitudes, is a mathematical methodology which allows complicated solution concepts to be executed using matrix operations and thus make attitudes more adaptable to a coding environment. When applied to environmental management conflicts, these innovative expansions of the attitudes framework illustrate the importance of cooperation and diplomacy in environmental conflict resolution.

This thesis presents a study into conflicts that emerge amongst sensor device rules when such devices are formed into networks. It describes conflicting patterns of communication and computation that can disturb the monitoring of subjects, and lower the quality of service. Such conflicts can negatively affect the lifetimes of the devices and cause incorrect information to be reported. A novel approach to detecting and resolving conflicts is presented. The approach is considered within the context of home-based psychiatric Ambulatory Assessment (AA). Rules are considered that can be used to control the behaviours of devices in a sensor network for AA. The research provides examples of rule conflict that can be found for AA sensor networks. Sensor networks and AA are active areas of research and many questions remain open regarding collaboration amongst collections of heterogeneous devices to collect data, process information in-network, and report personalised findings. This thesis presents an investigation into reliable rule-based service provisioning for a variety of stakeholders, including care providers, patients and technicians. It contributes a collection of rules for controlling AA sensor networks. This research makes a number of contributions to the field of rule-based sensor networks, including areas of knowledge representation, heterogeneous device support, system personalisation, and in particular, system reliability. This thesis provides evidence to support the conclusion that conflicts can be detected and resolved in adaptable rule-based sensor networks.

In a traditional safety impact analysis, it is necessary to have crash data on existing roadway conditions in the field and a few years must pass before accumulating reliable crash data. This is a time-consuming approach and there remains uncertainty in the crash data due to the random nature of crash occurrences. The Surrogate Safety Assessment Model (SSAM) was developed for resolving these issues. With SSAM, a conflict analysis is performed in a simulated environment. A planned improvement alternative under study is modeled and no physical installation of the alternative is needed. Hence, the method using a simulation software along with SSAM consumes less time compared to other traditional safety analysis methods that may require a physical installation of the new alternative and a long wait time for data collection. The purpose of this study is to evaluate if SSAM can be used to assess the safety of a highway segment or an intersection in term of the number and type of conflicts and to compare the safety effects of multiple access management alternatives with less time, less cost and less uncertainty than the traditional safety analysis methods. To meet the purpose of the study, two study sections, one on University Parkway in Orem and Provo and the other on Main Street in American Fork were selected and analyzed in this research. Based on the findings from the calibration of SSAM on the University Parkway study section, an evaluation of the effect of converting a TWLTL median into a raised median on a section of Main Street (US-89) from 300 West to 500 East in American Fork was performed using SSAM working on VISSIM simulation's trajectory files of the study section. This evaluation study was conducted to show how SSAM could be used to evaluate the effect of access management alternatives using surrogate safety measures. The analysis showed that a raised median would be much safer than a TWLTL median for the same level of traffic volume. Approximately a 32 to 50 percent reduction in the number of crossing conflicts was achieved when a raised median was used in lieu of a TWLTL median at the Main Street study section.