Defeasible Argumentation for Cooperative Multi-Agent Planning

Tesis por compendio[EN] Multi-Agent Systems (MAS), Argumentation and Automated Planning are three lines of investigations within the field of Artificial Intelligence (AI) that have been extensively studied over the last years. A MAS is a system composed of multiple intelligent agents that interact with each other and it is used to solve problems whose solution requires the presence of various functional and autonomous entities. Multi-agent systems can be used to solve problems that are difficult or impossible to resolve for an individual agent. On the other hand, Argumentation refers to the construction and subsequent exchange (iteratively) of arguments between a group of agents, with the aim of arguing for or against a particular proposal. Regarding Automated Planning, given an initial state of the world, a goal to achieve, and a set of possible actions, the goal is to build programs that can automatically calculate a plan to reach the final state from the initial state. The main objective of this thesis is to propose a model that combines and integrates these three research lines. More specifically, we consider a MAS as a team of agents with planning and argumentation capabilities. In that sense, given a planning problem with a set of objectives, (cooperative) agents jointly construct a plan to satisfy the objectives of the problem while they defeasibly reason about the environmental conditions so as to provide a stronger guarantee of success of the plan at execution time. Therefore, the goal is to use the planning knowledge to build a plan while agents beliefs about the impact of unexpected environmental conditions is used to select the plan which is less likely to fail at execution time. Thus, the system is intended to return collaborative plans that are more robust and adapted to the circumstances of the execution environment. In this thesis, we designed, built and evaluated a model of argumentation based on defeasible reasoning for planning cooperative multi-agent system. The designed system is independent of the domain, thus demonstrating the ability to solve problems in different application contexts. Specifically, the system has been tested in context sensitive domains such as Ambient Intelligence as well as with problems used in the International Planning Competitions.[ES] Dentro de la Inteligencia Artificial (IA), existen tres ramas que han sido ampliamente estudiadas en los últimos años: Sistemas Multi-Agente (SMA), Argumentación y Planificación Automática. Un SMA es un sistema compuesto por múltiples agentes inteligentes que interactúan entre sí y se utilizan para resolver problemas cuya solución requiere la presencia de diversas entidades funcionales y autónomas. Los sistemas multiagente pueden ser utilizados para resolver problemas que son difíciles o imposibles de resolver para un agente individual. Por otra parte, la Argumentación consiste en la construcción y posterior intercambio (iterativamente) de argumentos entre un conjunto de agentes, con el objetivo de razonar a favor o en contra de una determinada propuesta. Con respecto a la Planificación Automática, dado un estado inicial del mundo, un objetivo a alcanzar, y un conjunto de acciones posibles, el objetivo es construir programas capaces de calcular de forma automática un plan que permita alcanzar el estado final a partir del estado inicial. El principal objetivo de esta tesis es proponer un modelo que combine e integre las tres líneas anteriores. Más específicamente, nosotros consideramos un SMA como un equipo de agentes con capacidades de planificación y argumentación. En ese sentido, dado un problema de planificación con un conjunto de objetivos, los agentes (cooperativos) construyen conjuntamente un plan para resolver los objetivos del problema y, al mismo tiempo, razonan sobre la viabilidad de los planes, utilizando como herramienta de diálogo la Argumentación. Por tanto, el objetivo no es sólo obtener automáticamente un plan solución generado de forma colaborativa entre los agentes, sino también utilizar las creencias de los agentes sobre la información del contexto para razonar acerca de la viabilidad de los planes en su futura etapa de ejecución. De esta forma, se pretende que el sistema sea capaz de devolver planes colaborativos más robustos y adaptados a las circunstancias del entorno de ejecución. En esta tesis se diseña, construye y evalúa un modelo de argumentación basado en razonamiento defeasible para un sistema de planificación cooperativa multiagente. El sistema diseñado es independiente del dominio, demostrando así la capacidad de resolver problemas en diferentes contextos de aplicación. Concretamente el sistema se ha evaluado en dominios sensibles al contexto como es la Inteligencia Ambiental y en problemas de las competiciones internacionales de planificación.[CA] Dins de la intel·ligència artificial (IA), hi han tres branques que han sigut àmpliament estudiades en els últims anys: Sistemes Multi-Agent (SMA), Argumentació i Planificació Automàtica. Un SMA es un sistema compost per múltiples agents intel·ligents que interactúen entre si i s'utilitzen per a resoldre problemas la solución dels quals requereix la presència de diverses entitats funcionals i autònomes. Els sistemes multiagente poden ser utilitzats per a resoldre problemes que són difícils o impossibles de resoldre per a un agent individual. D'altra banda, l'Argumentació consistiex en la construcció i posterior intercanvi (iterativament) d'arguments entre un conjunt d'agents, amb l'objectiu de raonar a favor o en contra d'una determinada proposta. Respecte a la Planificació Automàtica, donat un estat inicial del món, un objectiu a aconseguir, i un conjunt d'accions possibles, l'objectiu és construir programes capaços de calcular de forma automàtica un pla que permeta aconseguir l'estat final a partir de l'estat inicial. El principal objectiu d'aquesta tesi és proposar un model que combine i integre les tres línies anteriors. Més específicament, nosaltres considerem un SMA com un equip d'agents amb capacitats de planificació i argumentació. En aquest sentit, donat un problema de planificació amb un conjunt d'objectius, els agents (cooperatius) construeixen conjuntament un pla per a resoldre els objectius del problema i, al mateix temps, raonen sobre la viabilitat dels plans, utilitzant com a ferramenta de diàleg l'Argumentació. Per tant, l'objectiu no és només obtindre automàticament un pla solució generat de forma col·laborativa entre els agents, sinó també utilitzar les creences dels agents sobre la informació del context per a raonar sobre la viabilitat dels plans en la seua futura etapa d'execució. D'aquesta manera, es pretén que el sistema siga capaç de tornar plans col·laboratius més robustos i adaptats a les circumstàncies de l'entorn d'execució. En aquesta tesi es dissenya, construeix i avalua un model d'argumentació basat en raonament defeasible per a un sistema de planificació cooperativa multiagent. El sistema dissenyat és independent del domini, demostrant així la capacitat de resoldre problemes en diferents contextos d'aplicació. Concretament el sistema s'ha avaluat en dominis sensibles al context com és la inte·ligència Ambiental i en problemes de les competicions internacionals de planificació.Pajares Ferrando, S. (2016). Defeasible Argumentation for Cooperative Multi-Agent Planning [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/60159TESISCompendi

A model checking-based approach for security policy verification of mobile systems

International audienceThis article describes an approach for the automated verification of mobile systems. Mobile systems are characterized by the explicit notion of (e.g., sites where they run) and the ability to execute at different locations, yielding a number of security issues. To this aim, we formalize mobile systems as Labeled Kripke Structures, encapsulating the notion of that describes the hierarchical nesting of the threads constituting the system. Then, we formalize a generic that includes rules for expressing and manipulating the code location. In contrast to many other approaches, our technique supports both access control and information flow specification. We developed a prototype framework for model checking of mobile systems. It works directly on the program code (in contrast to most traditional process-algebraic approaches that can model only limited details of mobile systems) and uses abstraction-refinement techniques, based also on location abstractions, to manage the program state space. We experimented with a number of mobile code benchmarks by verifying various security policies. The experimental results demonstrate the validity of the proposed mobile system modeling and policy specification formalisms and highlight the advantages of the model checking-based approach, which combines the validation of security properties with other checks, such as the validation of buffer overflows

Decision Taking for Selling Thread Startup

Decision Taking is discussed in the context of the role it may play for a selling agent in a search market, in particular for agents involved in the sale of valuable and relatively unique items, such as a dwelling, a second hand car, or a second hand recreational vessel. Detailed connections are made between the architecture of decision making processes and a sample of software technology based concepts including instruction sequences, multi-threading, and thread algebra. Ample attention is paid to the initialization or startup of a thread dedicated to achieving a given objective, and to corresponding decision taking. As an application, the selling of an item is taken as an objective to be achieved by running a thread that was designed for that purpose

Defeasible-argumentation-based multi-agent planning

[EN] This paper presents a planning system that uses defeasible argumentation to reason about context information during the construction of a plan. The system is designed to operate in cooperative multi-agent environments where agents are endowed with planning and argumentation capabilities. Planning allows agents to contribute with actions to the construction of the plan, and argumentation is the mechanism that agents use to defend or attack the planning choices according to their beliefs. We present the formalization of the model and we provide a novel specification of the qualification problem. The multi-agent planning system, which is designed to be domain-independent, is evaluated with two planning tasks from the problem suites of the International Planning Competition. We compare our system with a non-argumentative planning framework and with a different approach of planning and argumentation. The results will show that our system obtains less costly and more robust solution plans.This work has been partly supported by the Spanish MINECO under project TIN2014-55637-C2-2-R and the Valencian project PROMETEO II/2013/019.Pajares Ferrando, S.; Onaindia De La Rivaherrera, E. (2017). Defeasible-argumentation-based multi-agent planning. Information Sciences. 411:1-22. https://doi.org/10.1016/j.ins.2017.05.014S12241

Control of Dioxins From the Pulp and Paper Industry Under the Clean Water Act and Lead in Soil at Superfund Mining Sites: Two Case Studies in EPA's Use of Science

This paper discusses EPA's acquisition and use of science in addressing dioxins (and other organochlorines) from the pulp and paper industry under the Clean Water Act and lead in soil at large Superfund mining sites. The common thread between both cases is the challenge posed by administering national pollution control programs while considering site-by-site variability in factors that influence environmental risks. In the first case study, high levels of dioxin in fish downstream of pulp and paper mills were inadvertently detected in 1983 as part of an EPA effort to determine background levels of dioxin in areas presumed to be relatively uncontaminated. These findings quickly got the release of dioxins from pulp and paper mills on EPA's research agenda. News reports beginning in 1987 elevated the issue onto the regulatory agenda, but more than a decade has passed without EPA taking final regulatory action. Meanwhile, the pulp and paper industry has dramatically reduced, but not eliminated, dioxin discharges from mills. The key scientific issue now confronting EPA decisionmakers is how much weight to give to a water quality indicator called AOX. AOX is not statistically related to dioxin at the levels under consideration. Environmentalists justify using AOX because it serves as a surrogate measure for the entire toxicologically uncharacterized "soup" of organocholorines discharged from bleaching mills. Additionally, EPA estimates that discharges of dioxin from plants at levels below the analytical detection limits will continue to result in exceedances of stringent federal ambient water quality criteria under some local conditions. Industry counters that reductions in AOX do not achieve any measurable or monetizable environmental benefits. This case illustrates EPA's use of science to evaluate the cost-effectiveness of nominally technology-based water pollution controls. In the second case study, the Superfund program does not have the option of following its standard operating procedures for evaluating risks and determining Preliminary Remediation Goals for lead-contaminated sites because EPA has no numerical health-based standard for ingested lead (the agency's goal for lead is based on the level of lead in children's bloodstream). The study, therefore, illuminates the challenges and opportunities posed by developing and using rigorous site-specific scientific information. Potentially Responsible Parties (PRPs) generated rodent bioassay data which suggested that the bioavailability of lead in soil at mining sites would be much lower than EPA's default assumption. However, the agency disputed the validity of using mature rodents as animals models for the population of concern, children. In response, EPA conducted experiments with juvenile swine. The results indicated considerable variability in the bioavailability of lead in soil among the sites tested, with some higher, some lower, and some about the same as the agency's default assumption. Consequently, EPA cannot generalize across sites where similar mining activities occurred or draw any general distinctions between different types of mining sites, as had been presumed. This case illustrates that selection of the most appropriate animal model for toxicological studies involves tradeoffs between cost, experimental power and control, fidelity to human physiology, and the value of information for decision-making. Determination of the "optimal" animal model depends on the evaluative criterion being used. Although the new scientific data generated by EPA suggests higher bioavailability of lead in soil at some sites than the agency's default assumption, in terms of the final remedy selection, it appears that all of the results will be either beneficial or essentially neutral to Large Area Lead Site PRPs because EPA deems the cost of removing the contaminated soil to be excessive.

Forum Session at the First International Conference on Service Oriented Computing (ICSOC03)

The First International Conference on Service Oriented Computing (ICSOC) was held in Trento, December 15-18, 2003. The focus of the conference ---Service Oriented Computing (SOC)--- is the new emerging paradigm for distributed computing and e-business processing that has evolved from object-oriented and component computing to enable building agile networks of collaborating business applications distributed within and across organizational boundaries. Of the 181 papers submitted to the ICSOC conference, 10 were selected for the forum session which took place on December the 16th, 2003. The papers were chosen based on their technical quality, originality, relevance to SOC and for their nature of being best suited for a poster presentation or a demonstration. This technical report contains the 10 papers presented during the forum session at the ICSOC conference. In particular, the last two papers in the report ere submitted as industrial papers