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Pietro Torasso

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21 papers
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21

IJCAI Conference 2015 Conference Paper

Deordering and Numeric Macro Actions for Plan Repair

  • Enrico Scala
  • Pietro Torasso

The paper faces the problem of plan repair in presence of numeric information, by providing a new method for the intelligent selection of numeric macro actions. The method relies on a generalization of deordering, extended with new conditions accounting for dependencies and threats implied by the numeric components. The deordering is used as a means to infer (hopefully) minimal ordering constraints then used to extract independent and informative macro actions. Each macro aims at compactly representing a sub-solution for the overall planning problem. To verify the feasibility of the approach, the paper reports experiments in various domains from the International Planning Competition. Results show (i) the competitiveness of the strategy in terms of coverage, time and quality of the resulting plans wrt current approaches, and (ii) the actual independence from the planner employed.

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ECAI Conference 2014 Conference Paper

Proactive and Reactive Reconfiguration for the Robust Execution of Multi Modality Plans

  • Enrico Scala
  • Pietro Torasso

The paper addresses the problem of executing a plan in a dynamic environment for tasks involving constraints on consumable resources modeled as numeric fluents. In particular, the paper proposes a novel monitoring and adaptation strategy joining reactivity and proactivity in a unified framework. By exploiting the flexibility of a multi modality plan (where each action can be executed in different modalities), reactivity and proactivity are guaranteed by means of a reconfiguration step. The reconfiguration is performed (i) when the plan is no more valid to recovery from the impasse (reactively), or (ii) under the lead of a kernel based strategy to enforce the tolerance to unexpected situations (proactivity). Both mechanisms have been integrated into a continual planning system and experimentally evaluated over three numeric domains, extensions of planning competition domains. Results show that the approach is able to increase the percentage of cases successfully solved while preserving efficiency in most situations.

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ECAI Conference 2008 Conference Paper

Monitoring the Execution of a Multi-Agent Plan: Dealing with Partial Observability

  • Roberto Micalizio
  • Pietro Torasso

The paper addresses the task of monitoring and diagnosing the execution of a multi-agent plan (MAP) which involves actions concurrently executed by a team of cooperating agents. The paper describes a weak commitment strategy to deal with cases where observability is only partial and it is not sufficient for inferring the outcome of all the actions executed so far. The paper discusses the role of target actions in providing sufficient conditions for inferring the pending outcomes in a finite time window. The action outcome provides the basis for computing plan diagnosis and for singling out the goals which will not be achieved because of an action failure.

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AAMAS Conference 2008 Conference Paper

Supervision and Diagnosis of Joint Actions in Multi-Agent Plans

  • Roberto Micalizio
  • Pietro Torasso

The paper formalizes a distributed approach to the problem of supervising the execution of a multi-agent plan where (possibly joint) actions are executed concurrently by a team of cooperating agents in a partially observable environment. The notions of plan and agent diagnosis are introduced and discussed.

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AIJ Journal 2004 Journal Article

Multi-modal diagnosis combining case-based and model-based reasoning: a formal and experimental analysis

  • Luigi Portinale
  • Diego Magro
  • Pietro Torasso

Integrating different reasoning modes in the construction of an intelligent system is one of the most interesting and challenging aspects of modern AI. Exploiting the complementarity and the synergy of different approaches is one of the main motivations that led several researchers to investigate the possibilities of building multi-modal reasoning systems, where different reasoning modalities and different knowledge representation formalisms are integrated and combined. Case-Based Reasoning (CBR) is often considered a fundamental modality in several multi-modal reasoning systems; CBR integration has been shown very useful and practical in several domains and tasks. The right way of devising a CBR integration is however very complex and a principled way of combining different modalities is needed to gain the maximum effectiveness and efficiency for a particular task. In this paper we present results (both theoretical and experimental) concerning architectures integrating CBR and Model-Based Reasoning (MBR) in the context of diagnostic problem solving. We first show that both the MBR and CBR approaches to diagnosis may suffer from computational intractability, and therefore a careful combination of the two approaches may be useful to reduce the computational cost in the average case. The most important contribution of the paper is the analysis of the different facets that may influence the entire performance of a multi-modal reasoning system, namely computational complexity, system competence in problem solving and the quality of the sets of produced solutions. We show that an opportunistic and flexible architecture able to estimate the right cooperation among modalities can exhibit a satisfactory behavior with respect to every performance aspect. An analysis of different ways of integrating CBR is performed both at the experimental and at the analytical level. On the analytical side, a cost model and a competence model able to analyze a multi-modal architecture through the analysis of its individual components are introduced and discussed. On the experimental side, a very detailed set of experiments has been carried out, showing that a flexible and opportunistic integration can provide significant advantages in the use of a multi-modal architecture.

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IJCAI Conference 2003 Conference Paper

Automatic Abstraction in Component-Based Diagnosis Driven by System Observability

  • Gianluca Torta
  • Pietro Torasso

The paper addresses the problem of automatic abstraction of component variables in the context of Model Based Diagnosis, in order to produce models capable of deriving fewer and more general diagnoses when the current observabil­ ity of the system is reduced. The notion of indiscriminability among faults of a set of compo­ nents is introduced and constitutes the basis for a formal definition of admissible abstractions which preserve all the distinctions that are rel­ evant for diagnosis given the current observabil­ ity of the system. The automatic synthesis of abstract models further restricts abstractions such that the behavior of abstract components is expressed in terms of a simple and intuitive combination of the behavior of their subcom­ ponents. As a validation of our proposal, we present experimental results which show the re­ duction in the number of diagnoses returned by a diagnostic agent for a space robotic arm.

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AIIM Journal 2001 Journal Article

Multiple representations and multi-modal reasoning in medical diagnostic systems

  • Pietro Torasso

The paper examines the motivations for developing medical diagnostic systems exploiting multiple representations and multi-modal reasoning. The analysis is carried on by revisiting the architectural choices of the CHECK system (developed in late 1980s) which combined heuristic and causal knowledge. The results in the theory of diagnosis and in model-based reasoning (MBR) obtained in early 1990s are used for providing a formal characterization of the notion of diagnosis and of the reasoning mechanisms used in CHECK. The paper addresses also the problem of replacing heuristic knowledge provided by human experts with operational knowledge automatically derived from the deep model. In particular, the pros and cons of knowledge compilation and of the integration of case-based reasoning (CBR) with MBR are discussed by summarizing the experience gained in developing AID and ADAPtER. The problem of using an explicit representation of time in diagnostic systems is analyzed and recent work on the different characterizations of diagnosis arising when the temporal dimension is considered is reported. Finally, the implications of the results obtained in MBR and in temporal reasoning on the future of medical diagnostic systems are briefly discussed.

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IJCAI Conference 1999 Conference Paper

Diagnosis as a Variable Assignment Problem: A Case Study in a Space Robot Fault Diagnosis

  • Luigi Portinale
  • Pietro Torasso

In the present paper we introduce the notion of Variable Assignment Problem (VAP) as an abstract framework for characterizing diagnosis. Components of the system to be diagnosed are put in correspondence with variables, behavioral modes of the components are the values of the variables and a diagnosis is a variable assignment which explains the observations of the diagnostic problem, by considering the constraints put by the domain theory. In order to have a concise representation of diagnoses and to reduce the search space, we introduce the notion of scenario for representing a set of diagnoses. The paper discusses the definition of preference criteria for ranking solutions and their use for guiding the heuristic search for diagnoses. Experimental data are reported for the evaluation of such a heuristic search on a real-world diagnostic problem, concerning the identification of faults in a space robot arm; in this domain, where a high number of diagnoses may be possible, our approach allows one to get a concise representation of the large number of solutions and to define effective diagnostic strategies able to provide relevant information about fault localization and identification.

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AIIM Journal 1991 Journal Article

On the co-operation between abductive and temporal reasoning in medical diagnosis

  • Luca Console
  • Pietro Torasso

On of the basic (and often implicit) assumptions of most first generation diagnostic expert systems is that they operate in a static environment. However, the static domain assumption is very limiting since it requires that all manifestations are observable (and observed) at a unique time point in order to perform diagnosis (and this is unrealistic in medical applications). The adoption of deep and causal models in second generation expert systems provided some insights into how to deal with time in the diagnostic process. There is, in fact, a strong relationship between the notion of causation and the notion of time. In the paper we present an architecture for diagnostic problem solving based on the use of a pathophysiological model in which both causal and temporal relations are explicitly represented. In particular, the architecture is an extension of the causal component of CHECK which has been used to model pathophysiology in the fields of cirrhosis and leprosis. We show that in such an extended framework diagnostic problems can be solved correctly only by means of a strict co-operation between abductive and temporal reasoning. The complexity of such forms of reasoning is analysed and some sources of complexity are singled out. Possible restrictions of the representation formalism are presented and forms of temporal reasoning providing approximate solutions are discussed.

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AIIM Journal 1990 Journal Article

A report on medical expert systems research in Italy

  • Pietro Torasso

The paper describes the main projects developed in Italy in the field of Artificial Intelligence in Medicine. Particular attention is given to expert systems for clinical applications. Some projects in the field of Health Care are also mentioned. The presentation will follow a chronological order, starting from the late seventies and focusing on the research carried out over the last four years.

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AIIM Journal 1989 Journal Article

Dealing with uncertain knowledge in medical decision-making: A case study in hepatology

  • Leonardo Lesmo
  • Lorenza Saitta
  • Pietro Torasso

It has widely been recognized that knowledge-based expert systems need efficient mechanisms to model the uncertainty associated with many decision-making activities. Such a need is particularly urgent in medicine. In this paper, we present an approach based on fuzzy logic to give a possible solution to this problem; its pros and cons are discussed by taking into account the experience gained in developing LITO1 and LITO2, two expert systems devoted to the assessment of the liver function and to the diagnosis of hepatic diseases. The advantages of mixing fuzzy production rules with frame-like structures (introduced for representing the clinical data) are discussed. In particular, the use of fuzzy linguistic variables for modeling the possible values of the clinical data is described: this allows, for a clear and perspicuous description of the correspondence between quantitative and qualitative expressions. Furthermore, different alternatives for evaluating and combining evidence are reviewed. Finally, the need of introducing frame structures also for representing diagnostic hypotheses is discussed, together with the problem of evaluating the fuzzy match between the prototypical description of a diagnostic hypothesis and the data describing the status of the specific patient under examination.

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IJCAI Conference 1985 Conference Paper

Weighted Interaction of Syntax and Semantics in Natural Language Analysis

  • Leonardo Lesmo
  • Pietro Torasso

The present paper discusses the extensions to the parsing strategies adopted for FIDO (a Flexible Interface for Database Operations). The parser is able to deal with ill-formed inputs (syntactically i l l - formed sentences, fragments, conjunctions, etc.) because of the strict cooperation among syntax and semantics. The syntactic knowledge is represented by means of packets of condition-action rules associated with syntactic categories. The non-determinism is mainly handled by means of rules which restructure the parse tree (called "natural changes") so that the use of backtracking is strongly limited. In order to deal with d i f f i c u l t cases in which no clear-cut mechanism exists for excluding an interpretation, a weighting mechanism has been added to the parser so that it is possible to explore few different hypotheses in parallel and to choose the best one on the basis of complex interaction among syntax and semantics.

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