Assumption-based Truth Maintenance System Research Articles

Adaptive Fuzzy Interpolation

Fuzzy interpolative reasoning strengthens the power of fuzzy inference by the enhancement of the robustness of fuzzy systems and the reduction of the systems’ complexity. However, after a series of interpolations, it is possible that multiple object values for a common variable are inferred, leading to inconsistency in interpolated results. Such inconsistencies may result from defective interpolated rules or incorrect interpolative transformations. This paper presents a novel approach for identification and correction of defective rules in interpolative transformations, thereby removing the inconsistencies. In particular, an assumption-based truth-maintenance system (ATMS) is used to record dependences between interpolations, and the underlying technique that the classical general diagnostic engine (GDE) employs for fault localization is adapted to isolate possible faulty interpolated rules and their associated interpolative transformations. From this, an algorithm is introduced to allow for the modification of the original linear interpolation to become first-order piecewise linear. The approach is applied to a realistic problem, which predicates the diarrheal disease rates in remote villages, to demonstrate the potential of this study.

Large Scale Diagnosis Using Associations between System Outputs and Components

Model-based diagnosis (MBD) uses an abstraction of system to diagnose possible faulty functions of an underlying system. To improve the solution efficiency for multi-fault diagnosis problems, especially for large scale systems, this paper proposes a method to induce reasonable diagnosis solutions, under coarse diagnosis, by using the relationships between system outputs and components. Compared to existing diagnosis methods, the proposed framework only needs to consider associations between outputs and components by using an assumption-based truth maintenance system (ATMS) [de Kleer 1986] to obtain correlation components for every output node. As a result, our method significantly reduces the number of variables required for model diagnosis, which makes it suitable for large scale circuit systems.

AN INTEGRATED FRAMEWORK FOR SUSPECT INVESTIGATION

In a complex crime scene with many possible suspects and conflicting evidence, crime investigation requires scientific and logical steps to narrow down the suspects. Since human investigators have difficulty in fully handling all reasoning in this highly complex hypothesis space, we propose a decision support system to aid the investigation process. The system integrates a rule-based reasoner, a Bayesian network for criminal profiling, and an assumption-based truth maintenance system for evidential reasoning to determine the most plausible suspect. The reasoning process reasons about a profiling classification and an alibi credibility measure. It proved effective in a realistic simulation.

A Credibilistic Approach to Assumption-Based Truth Maintenance

This paper presents an extension of the assumption-based truth maintenance system (ATMS), called ATMS, which has the capability to cope with uncertain justifications and assumptions. Such justifications and assumptions are represented and dealt with in the framework of credibility theory. Important concepts in ATMS such as environments, labels, logical consequences, and consistency are redefined by the use of credibility measure. Based on these concepts, the label-updating procedure of the classical ATMS is extended, allowing effective computation of the membership function of any node within the network and that of its supporting environment. In addition, the contradictory environments can be captured with respect to their inconsistency degrees. This paper is compared to the most relevant existing research (i.e., ATMS using necessity as the truth value and ATMS using possibility as the truth value), demonstrating the significant improvements made. This paper also presents an illustrative application of credibilistic ATMS in supporting automated construction of domain models.

An Assumption-based Truth Maintenance System in ActiveAid for UNIX Users

This paper deals with the problem of assigning meaning to the interaction of a user with a command-driven system such as UNIX. This research is part of the construction of an active intelligent help system that monitors users in order to offer spontaneous help when they are facing problems. In order to ensure this, the help system must build and maintain a model of the user. We describe a mechanism that is used by the user modelling component of such a help system. This mechanism makes explicit assumptions about the user which account for different hypotheses about what the user is actually thinking at every stage of the interaction. The consistency of these assumptions is managed by an Assumption-based Truth Maintenance System (ATMS). The selection between a number of different user models is based on the information which is extracted from the feedback that UNIX provides in response to user actions.

Animated interface agent applying atms-based multimodal input interpretation

Two requirements should be met in order to develop a practical multimodal interface system , i . e ., ( 1 ) integration of delayed arrival of data and ( 2 ) elimination of ambiguity in recognition results of each modality . This paper presents an efficient and generic methodology for interpretation of multimodal input to satisfy these requirements . The proposed methodology can integrate delayed - arrival data satisfactorily and efficiently interpret multimodal input that contains ambiguity . In the input interpretation the multimodal interpretation process is regarded as hypothetical reasoning , and the control mechanismof interpretation is formalized by applying the assumption - based truth maintenance system ( ATMS ). The proposed method is applied to an interface agent system that accepts multimodal input consisting of voice and direct indication gesture on a touch display . The systemcommunicates to the user through a human - like interface agent's three - dimensional motion image with facial expressions , gestures , and a synthesized voice .

Ontologies are not the Panacea in Data Integration: A FlexibleCoordinator to Mediate Context Construction

Shared ontologies describe concepts and relationships to resolve semantic conflicts amongst users accessing multiple autonomous and heterogeneous information sources. We contend that while ontologies are useful in semantic reconciliation, they do not guarantee correct classification of semantic conflicts, nor do they provide the capability to handle evolving semantics or a mechanism to support a dynamic reconciliation process. Their limitations are illustrated through a conceptual analysis of several prominent examples used in heterogeneous database systems and in natural language processing. We view semantic reconciliation as a nonmonotonic query-dependent process that requires flexible interpretation of query context, and as a mechanism to coordinate knowledge elicitation while constructing the query context. We propose a system that is based on these characteristics, namely the SCOPES (Semantic Coordinator Over Parallel Exploration Spaces) system. SCOPES takes advantage of ontologies to constrain exploration of a remote database during the incremental discovery and refinement of the context within which a query can be answered. It uses an Assumption-based Truth Maintenance System (ATMS) to manage the multiple plausible contexts which coexist while the semantic reconciliation process is unfolding, and the Dempster-Shafer (DS) theory of belief to model the likelihood of these plausible contexts.

A possibilistic ATMS contribution to diagnose analog electronic circuits

Model-based diagnosis theory allows one to diagnose a system just by using the equations which describe the system structure and the correct behavior models of system components. CATS is an algorithm which implements the model-based diagnosis theory in the framework of interval arithmetic. Simple or multiple faults in an analog electronic circuit can be isolated. This research aims at showing the possibilistic theory advantage in the framework of CATS. In order to do this, we have written a program similar to CATS, except that it uses a possibilistic Assumption-based Truth Maintenance System. © 1997 John Wiley & Sons, Inc.

The common order-theoretic structure of version spaces and ATMSs

We demonstrate how order-theoretic abstractions can be useful in identifying, formalizing, and exploiting relationships between seemingly dissimilar AI algorithms that perform computations on partially-ordered sets. In particular, we show how the order-theoretic concept of an anti-chain can be used to provide an efficient representation for such sets when they satisfy certain special properties. We use anti-chains to identify and analyze the basic operations and representation optimizations in the version space learning algorithm and the assumption-based truth maintenance system (ATMS). Our analysis allows us to (1) extend the known theory of admissibility of concept spaces for incremental version space merging, and (2) develop new, simpler label-update algorithms for ATMSs with DNF assumption formulas.

A cell-based approach for generating solid objects from orthographic projections

This paper describes an efficient method for converting orthographic projections into solid models based on non-manifold topology and the assumption-based truth maintenance system (ATMS), and then describes an error recovery method for incorrect orthographic projections. A combination of non-manifold modelling and ATMS achieves excellent performance for conversion problems. In our method, all solid candidates are maintained by a cellular model using non-manifold topology. Since a combination of cells in a cellular model determines the shape of a solid, solid models that match orthographic projections can be derived by solving constraints between cells and orthographic projections. A sufficient group of constraints can be expressed as a set of Boolean equations, which can be solved efficiently by using ATMS. Our method can even be applied to incorrect draftings. In actual design, many draftings contain human errors, but conventional methods cannot handle such incorrect draftings. We discuss methods for detecting inconsistent lines that should not have been included, or missing lines that should have been included.

A cooperative problem-solver for investment management

Classical expert systems which are acting as autonomous problem-solvers are unsuitable when the problem needs to be solved cooperatively and when the users of the system are themselves experts. As a consequence a new type of system is emerging—the cooperative problem-solving system. This paper details the development of a cooperative problem-solving system for the domain of investment management. Much of investment management involves comparing alternative solutions. An assumption-based truth maintenance system (ATMS), which allows multiple hypothetical scenarios to be modelled, is the technique used to store each agents portfolio solution, constraints and underlying decisions. Analysis of transcripts obtained during knowledge acquisition revealed seven functions that a cooperative problem-solving system should seek to provide. The resulting system provides a cooperative environment in which multiple users can investigate and compare different solution, build new approaches to obtaining a solution and introduce new concepts to engender discussion.

An assumption-based truth maintenance system dealing with non-ground justifications

The assumption-based truth maintenance system (ATMS) is a reasoning maintenance system proved useful in many applications and fields such as diagnosis and abductive reasoning. However, one limitation of the ATMS is that it handles propositional justifications only. There are problems, instead, where one has to move to the first-order predicate calculus, and explicitly consider variables. In this paper, we present an extension of the basic ATMS where justifications are definite Horn clauses possibly containing variables, and non-ground terms can occur in ATMS data structures. To maintain the incrementality feature peculiar to the ATMS, we extend the basic label-updating algorithm from the propositional case to the first-order one. In this way, we obtain a system able to produce, for a given atomic formula, the set of minimal hypotheses (possibly containing variables) we have to add to a given theory to prove this formula. We show how this extension relates to logic programs when they are optimized through ...

An intelligent assistant for nuclear test ban treaty verification

To assist underground nuclear test ban treaty verification specialists, we are developing technologies for automatically processing seismic monitoring data. The intelligent assistant described in this paper, called the Seismic Event Analyzer (SEA), isolates "interesting" events by filtering large volumes of continuously arriving data. It also uses an assumption-based truth maintenance system to emulate the human analyst's problem-solving behavior.

Reason Maintenance in Product Modeling

An approach to product modeling by using a reason maintenance system to reduce the amount of search required for the identification of feasible designs is described. An assumption-based truth maintenance system and multiple worlds are used to discover and store information about feasible designs and to avoid further consideration of infeasible design alternatives. An object-oriented computer program for product modeling is presented.

NOGOOD RECORDING FOR STATIC AND DYNAMIC CONSTRAINT SATISFACTION PROBLEMS

Many AI synthesis problems such as planning, scheduling or design may be encoded in a constraint satisfaction problems (CSP). A CSP is typically defined as the problem of finding any consistent labeling for a fixed set of variables satisfying all given constraints between these variables. However, for many real tasks, the set of constraints to consider may evolve because of the environment or because of user interactions. The notion of dynamic CSP (DCSP) [DD88] has been proposed to represent such evolutions. The problem we consider here is the solution maintenance problem in a DCSP. Naively applying usual satisfaction algorithms to this problem results in redundant search and inefficiency. A general approach to suppress redundancies in case of both restrictions and relaxations is to concisely represent the frontier of the solution space and justifications of this frontier in terms of set of constraints. This paper proposes a new class of constraint recording algorithms called nogood recording that may be used for solving both dynamic CSPs and usual CSP (called static CSPs here). It offers an interesting compromise, polynomially bounded in space, between an ATMS-like (Assumption-based Truth Maintenance System) approach, that would give a precise and exhaustive description of the frontier, and the usual constraint satisfaction algorithms (that discover a new frontier at each execution). We first introduce the principles used for nogood generation and then examine various recording schemes, on top of different tree search algorithms, characterizing the tradeoffs between the amount of recorded constraints and the pruning achieved. We then present experimental results and comparisons with various existing techniques for solving static or dynamic CSP.

Modelling and Control of Therapeutic System Using “Assumption Based Truth Maintenance System”

The salient features of a model based system in electrotherapy are discussed in this paper. The general frame-work of this dedicated model based system is to identify a device model and sub-system to set appropriate modules for diagnosis and therapy and to provide the control knowledge for selecting the appropriate facets of the model based on stimulation parameter, habituation response and type of electrode array. This system is not only effective but also optimally simple and in fact it has been observed that these qualitative reasoning methods are complete and do not miss any real value solution in spite of assuptions. assumptions.

Implementation Of a constraint System For modelling And Reasoning With Physical Systems

This paper describes a framework, called a constraint system, for representing physical systems and for reasoning about them. Presently, the system is limited to physical devices with static states. The constraint system allows us to represent models of physical devices, where a device is represented as a component-connection model, and each component is modeled by a set of constraints. New derivations are done by a technique called constraint propagation, where an initial set of values are propagated through the constraint space, leading to the derivation new values. The system is built using an Assumption- based Truth Maintenance System (ATMS), and it is useful for a variety of tasks, such as model-based diagnosis, model-based prediction, model-based simulation, analysis, etc.

Deductive efficiency, belief revision and acting

Abstract The SNePS inference engine is optimized for deductive efficiency, i.e. all beliefs acquired via inference are added to the agent's beliefs so that future queries may be answered by a retrieval rather than rederivation. An assumption-based truth maintenance system keeps track of the derivation histories of derived beliefs. We show how such an architecture simplifies the ontology of prepositional representations of plans; acts; preconditions, and effects of actions. In addition, the deductive efficiency of the basic system automatically extends itself to efficient search of plans, and hierarchical plan decompositions.

Multi-auditor cooperation: a model of distributed reasoning

Management and analysis of complex systems frequently involves groups of managers and experts, each working on different parts of the system, cooperating and coordinating among themselves to manage and analyze the system as a whole. The authors propose a distributed reasoning approach to render this process of multiagent cooperation more efficient and effective. They consider, as an example of such a group process, the auditing process in assessing the reliability of an internal control system in which each auditor makes default assumptions about parts of the system being analyzed by other team members. The coordination process is modeled using an assumption-based truth maintenance system, which explicitly represents such assumptions, their possible retractions on subsequent contrary evidence, and changes in the auditor's terminal options. The ways in which the resolution of opinions among auditors can be achieved through a process of evidence sharing facilitated by the model are discussed. >

Using a truth-maintenance system to assist product-model construction for design and process planning

Assistance with product-model construction is a fundamental task for computer-aided-design systems. A general mechanism for recording and manipulating model-construction process in computers is proposed in the paper. The model-construction process is considered as a series of model state transitions realized by modeling operations. This process can only be properly recorded with dependencies between the operations. The dependency information is automatically detected on the basis of the conditions necessary for the execution of an operation. An assumption-based truth-maintenance system is used as a tool for recording and manipulating the dependency. Two basic functions for assisting with model-construction activities, an undo function and a model-maintenance function, are realized by using the dependency in a uniform manner. The applicability of these functions is verified using interactive-solid-modeling and machining process-planning examples.