71 research outputs found
Abstraction in situation calculus action theories
We develop a general framework for agent abstraction based on the situation calculus and the ConGolog agent programming language. We assume that we have a high-level specification and a low-level specification of the agent, both repre- sented as basic action theories. A refinement mapping specifies how each high-level action is implemented by a low- level ConGolog program and how each high-level fluent can be translated into a low-level formula. We define a notion of sound abstraction between such action theories in terms of the existence of a suitable bisimulation between their respective models. Sound abstractions have many useful properties that ensure that we can reason about the agentâs actions (e.g., executability, projection, and planning) at the abstract level, and refine and concretely execute them at the low level. We also characterize the notion of complete abstraction where all actions (including exogenous ones) that the high level thinks can happen can in fact occur at the low level
Abstraction in situation calculus action theories
We develop a general framework for agent abstraction based on the situation calculus and the ConGolog agent programming language. We assume that we have a high-level specification and a low-level specification of the agent, both repre- sented as basic action theories. A refinement mapping specifies how each high-level action is implemented by a low- level ConGolog program and how each high-level fluent can be translated into a low-level formula. We define a notion of sound abstraction between such action theories in terms of the existence of a suitable bisimulation between their respective models. Sound abstractions have many useful properties that ensure that we can reason about the agentâs actions (e.g., executability, projection, and planning) at the abstract level, and refine and concretely execute them at the low level. We also characterize the notion of complete abstraction where all actions (including exogenous ones) that the high level thinks can happen can in fact occur at the low level
Verification of Generalized Inconsistency-Aware Knowledge and Action Bases (Extended Version)
Knowledge and Action Bases (KABs) have been put forward as a semantically
rich representation of a domain, using a DL KB to account for its static
aspects, and actions to evolve its extensional part over time, possibly
introducing new objects. Recently, KABs have been extended to manage
inconsistency, with ad-hoc verification techniques geared towards specific
semantics. This work provides a twofold contribution along this line of
research. On the one hand, we enrich KABs with a high-level, compact action
language inspired by Golog, obtaining so called Golog-KABs (GKABs). On the
other hand, we introduce a parametric execution semantics for GKABs, so as to
elegantly accomodate a plethora of inconsistency-aware semantics based on the
notion of repair. We then provide several reductions for the verification of
sophisticated first-order temporal properties over inconsistency-aware GKABs,
and show that it can be addressed using known techniques, developed for
standard KABs
Logic-Based Specification Languages for Intelligent Software Agents
The research field of Agent-Oriented Software Engineering (AOSE) aims to find
abstractions, languages, methodologies and toolkits for modeling, verifying,
validating and prototyping complex applications conceptualized as Multiagent
Systems (MASs). A very lively research sub-field studies how formal methods can
be used for AOSE. This paper presents a detailed survey of six logic-based
executable agent specification languages that have been chosen for their
potential to be integrated in our ARPEGGIO project, an open framework for
specifying and prototyping a MAS. The six languages are ConGoLog, Agent-0, the
IMPACT agent programming language, DyLog, Concurrent METATEM and Ehhf. For each
executable language, the logic foundations are described and an example of use
is shown. A comparison of the six languages and a survey of similar approaches
complete the paper, together with considerations of the advantages of using
logic-based languages in MAS modeling and prototyping.Comment: 67 pages, 1 table, 1 figure. Accepted for publication by the Journal
"Theory and Practice of Logic Programming", volume 4, Maurice Bruynooghe
Editor-in-Chie
Bounded Situation Calculus Action Theories
In this paper, we investigate bounded action theories in the situation
calculus. A bounded action theory is one which entails that, in every
situation, the number of object tuples in the extension of fluents is bounded
by a given constant, although such extensions are in general different across
the infinitely many situations. We argue that such theories are common in
applications, either because facts do not persist indefinitely or because the
agent eventually forgets some facts, as new ones are learnt. We discuss various
classes of bounded action theories. Then we show that verification of a
powerful first-order variant of the mu-calculus is decidable for such theories.
Notably, this variant supports a controlled form of quantification across
situations. We also show that through verification, we can actually check
whether an arbitrary action theory maintains boundedness.Comment: 51 page
Logic-based Technologies for Multi-agent Systems: A Systematic Literature Review
Precisely when the success of artiïŹcial intelligence (AI) sub-symbolic techniques makes them be identiïŹed with the whole AI by many non-computerscientists and non-technical media, symbolic approaches are getting more and more attention as those that could make AI amenable to human understanding. Given the recurring cycles in the AI history, we expect that a revamp of technologies often tagged as âclassical AIâ â in particular, logic-based ones will take place in the next few years.
On the other hand, agents and multi-agent systems (MAS) have been at the core of the design of intelligent systems since their very beginning, and their long-term connection with logic-based technologies, which characterised their early days, might open new ways to engineer explainable intelligent systems. This is why understanding the current status of logic-based technologies for MAS is nowadays of paramount importance.
Accordingly, this paper aims at providing a comprehensive view of those technologies by making them the subject of a systematic literature review (SLR). The resulting technologies are discussed and evaluated from two different perspectives: the MAS and the logic-based ones
Pseudo-contractions as Gentle Repairs
Updating a knowledge base to remove an unwanted consequence is a challenging task. Some of the original sentences must be either deleted or weakened in such a way that the sentence to be removed is no longer entailed by the resulting set. On the other hand, it is desirable that the existing knowledge be preserved as much as possible, minimising the loss of information. Several approaches to this problem can be found in the literature. In particular, when the knowledge is represented by an ontology, two different families of frameworks have been developed in the literature in the past decades with numerous ideas in common but with little interaction between the communities: applications of AGM-like Belief Change and justification-based Ontology Repair. In this paper, we investigate the relationship between pseudo-contraction operations and gentle repairs. Both aim to avoid the complete deletion of sentences when replacing them with weaker versions is enough to prevent the entailment of the unwanted formula. We show the correspondence between concepts on both sides and investigate under which conditions they are equivalent. Furthermore, we propose a unified notation for the two approaches, which might contribute to the integration of the two areas
Simulation and statistical model-checking of logic-based multi-agent system models
This thesis presents SALMA (Simulation and Analysis of Logic-Based Multi-
Agent Models), a new approach for simulation and statistical model checking
of multi-agent system models.
Statistical model checking is a relatively new branch of model-based approximative
verification methods that help to overcome the well-known scalability
problems of exact model checking. In contrast to existing solutions,
SALMA specifies the mechanisms of the simulated system by means of logical
axioms based upon the well-established situation calculus. Leveraging
the resulting first-order logic structure of the system model, the simulation
is coupled with a statistical model-checker that uses a first-order variant of
time-bounded linear temporal logic (LTL) for describing properties. This is
combined with a procedural and process-based language for describing agent
behavior. Together, these parts create a very expressive framework for modeling
and verification that allows direct fine-grained reasoning about the agentsâ
interaction with each other and with their (physical) environment.
SALMA extends the classical situation calculus and linear temporal logic
(LTL) with means to address the specific requirements of multi-agent simulation
models. In particular, cyber-physical domains are considered where
the agents interact with their physical environment. Among other things,
the thesis describes a generic situation calculus axiomatization that encompasses
sensing and information transfer in multi agent systems, for instance
sensor measurements or inter-agent messages. The proposed model explicitly
accounts for real-time constraints and stochastic effects that are inevitable in
cyber-physical systems.
In order to make SALMAâs statistical model checking facilities usable also
for more complex problems, a mechanism for the efficient on-the-fly evaluation
of first-order LTL properties was developed. In particular, the presented algorithm
uses an interval-based representation of the formula evaluation state
together with several other optimization techniques to avoid unnecessary computation.
Altogether, the goal of this thesis was to create an approach for simulation
and statistical model checking of multi-agent systems that builds upon
well-proven logical and statistical foundations, but at the same time takes a
pragmatic software engineering perspective that considers factors like usability,
scalability, and extensibility. In fact, experience gained during several small
to mid-sized experiments that are presented in this thesis suggest that the
SALMA approach seems to be able to live up to these expectations.In dieser Dissertation wird SALMA (Simulation and Analysis of Logic-Based
Multi-Agent Models) vorgestellt, ein im Rahmen dieser Arbeit entwickelter
Ansatz fuÌr die Simulation und die statistische ModellpruÌfung (Model Checking)
von Multiagentensystemen.
Der Begriff âStatistisches Model Checkingâ beschreibt modellbasierte approximative
Verifikationsmethoden, die insbesondere dazu eingesetzt werden
können, um den unvermeidlichen Skalierbarkeitsproblemen von exakten Methoden
zu entgehen. Im Gegensatz zu bisherigen AnsÀtzen werden in SALMA die
Mechanismen des simulierten Systems mithilfe logischer Axiome beschrieben,
die auf dem etablierten SituationskalkuÌl aufbauen. Die dadurch entstehende
prÀdikatenlogische Struktur des Systemmodells wird ausgenutzt um ein Model
Checking Modul zu integrieren, das seinerseits eine prÀdikatenlogische Variante
der linearen temporalen Logik (LTL) verwendet. In Kombination mit
einer prozeduralen und prozessorientierten Sprache fuÌr die Beschreibung von
Agentenverhalten entsteht eine ausdrucksstarke und flexible Plattform fuÌr die
Modellierung und Verifikation von Multiagentensystemen. Sie ermöglicht eine
direkte und feingranulare Beschreibung der Interaktionen sowohl zwischen
Agenten als auch von Agenten mit ihrer (physischen) Umgebung.
SALMA erweitert den klassischen SituationskalkuÌl und die lineare temporale
Logik (LTL) um Elemente und Konzepte, die auf die spezifischen Anforderungen
bei der Simulation und Modellierung von Multiagentensystemen
ausgelegt sind. Insbesondere werden cyber-physische Systeme (CPS) unterstuÌtzt,
in denen Agenten mit ihrer physischen Umgebung interagieren. Unter
anderem wird eine generische, auf dem SituationskalkuÌl basierende, Axiomatisierung
von Prozessen beschrieben, in denen Informationen innerhalb von
Multiagentensystemen transferiert werden â beispielsweise in Form von Sensor-
Messwerten oder Netzwerkpaketen. Dabei werden ausdruÌcklich die unvermeidbaren
stochastischen Effekte und Echtzeitanforderungen in cyber-physischen
Systemen beruÌcksichtigt.
Um statistisches Model Checking mit SALMA auch fuÌr komplexere Problemstellungen
zu ermöglichen, wurde ein Mechanismus fuÌr die effiziente Auswertung
von prÀdikatenlogischen LTL-Formeln entwickelt. Insbesondere beinhaltet
der vorgestellte Algorithmus eine Intervall-basierte ReprÀsentation des
Auswertungszustands, sowie einige andere OptimierungsansÀtze zur Vermeidung
von unnötigen Berechnungsschritten.
Insgesamt war es das Ziel dieser Dissertation, eine Lösung fuÌr Simulation
und statistisches Model Checking zu schaffen, die einerseits auf fundierten
logischen und statistischen Grundlagen aufbaut, auf der anderen Seite jedoch
auch pragmatischen Gesichtspunkten wie Benutzbarkeit oder Erweiterbarkeit
genuÌgt. TatsĂ€chlich legen erste Ergebnisse und Erfahrungen aus
mehreren kleinen bis mittelgroĂen Experimenten nahe, dass SALMA diesen
Zielen gerecht wird
Probabilistic Hybrid Action Models for Predicting Concurrent Percept-driven Robot Behavior
This article develops Probabilistic Hybrid Action Models (PHAMs), a realistic
causal model for predicting the behavior generated by modern percept-driven
robot plans. PHAMs represent aspects of robot behavior that cannot be
represented by most action models used in AI planning: the temporal structure
of continuous control processes, their non-deterministic effects, several modes
of their interferences, and the achievement of triggering conditions in
closed-loop robot plans.
The main contributions of this article are: (1) PHAMs, a model of concurrent
percept-driven behavior, its formalization, and proofs that the model generates
probably, qualitatively accurate predictions; and (2) a resource-efficient
inference method for PHAMs based on sampling projections from probabilistic
action models and state descriptions. We show how PHAMs can be applied to
planning the course of action of an autonomous robot office courier based on
analytical and experimental results
infinite states verification in game-theoretic logics
Many practical problems where the environment is not in the system's control such as service orchestration and contingent and multi-agent planning can be modelled in game-theoretic logics. This thesis demonstrates that the verification techniques based on regression and fixpoint approximation introduced in De Giacomo, Lesperance and Pearce [DLP10] do work on several game-theoretic problems. De Giacomo, Lesperance and Pearce [DLP10] emphasize that their study is essentially theoretical and call for complementing their work with experimental studies to understand whether these techniques are effective in practical cases. Several example problems with varying properties have been developed and, although not exhaustive nor complete,, our results nevertheless demonstrate that the techniques work on some problems. Our results show that the methods introduced in [DLP10] work for infinite domains where very few verification methods are available and allow reasoning about a wide range of game problems. Our examples also demonstrate the use of a rich language for specifying temporal properties proposed in [DLP10]. While classical model checking is well known and utilized, it is mostly restricted to finite-state models. A important aspect of the work is the demonstration of the use and effectiveness of characteristic graphs (ClaBen and Lakemeyer [CL08]) in verifying properties of games in infinite domains. A special-purpose programming language GameGolog proposed in De Giacomo, Lesperance and Pearce [DLP10] allows such game-theoretic systems to be specified procedurally at a high-level of abstraction. We show its practicality to model game structures in a convenient way that combines declarative and procedural elements. We provided examples to show the verification of GameGolog specifications using characteristic graphs. This thesis also proposes a refinement to the formalism in [DLP10] to incorporate action constraints as a mechanism to incorporate user strategies and for the modeller to supply heuristic guidance in temporal property verification. It also presents an implementation of evaluation-based fixpoint verifier that handles Situation Calculus game structures, as well as GameGolog specifications, for temporal property verification in the initial or a given situation. The verifier supports player action constraints
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