Multiagent simple temporal problem: The arc-consistency approach

Copyright © 2018, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. The Simple Temporal Problem (STP) is a fundamental temporal reasoning problem and has recently been extended to the Multiagent Simple Temporal Problem (MaSTP). In this paper we present a novel approach that is based on enforcing arc-consistency (AC) on the input (multiagent) simple temporal network. We show that the AC-based approach is sufficient for solving both the STP and MaSTP and provide efficient algorithms for them. As our AC-based approach does not impose new constraints between agents, it does not violate the privacy of the agents and is superior to the state-of-the-art approach to MaSTP. Empirical evaluations on diverse benchmark datasets also show that our AC-based algorithms for STP and MaSTP are significantly more efficient than existing approaches

A Survey of Multi-Robot Motion Planning

Multi-robot Motion Planning (MRMP) is an active research field which has gained attention over the years. MRMP has significant roles to improve the efficiency and reliability of multi-robot system in a wide range of applications from delivery robots to collaborative assembly lines. This survey provides an overview of MRMP taxonomy, state-of-the-art algorithms, and approaches which have been developed for multi-robot systems. This study also discusses the strengths and limitations of each algorithm and their applications in various scenarios. Moreover, based on this, we can draw out open problems for future research.Comment: This is my Ph.D. comprehensive exam repor

Optimising Flexibility of Temporal Problems with Uncertainty

Temporal networks have been applied in many autonomous systems. In real situations, we cannot ignore the uncertain factors when using those autonomous systems. Achieving robust schedules and temporal plans by optimising flexibility to tackle the uncertainty is the motivation of the thesis. This thesis focuses on the optimisation problems of temporal networks with uncertainty and controllable options in the field of Artificial Intelligence Planning and Scheduling. The goal of this thesis is to construct flexibility and robustness metrics for temporal networks under the constraints of different levels of controllability. Furthermore, optimising flexibility for temporal plans and schedules to achieve robust solutions with flexible executions. When solving temporal problems with uncertainty, postponing decisions according to the observations of uncertain events enables flexible strategies as the solutions instead of fixed schedules or plans. Among the three levels of controllability of the Simple Temporal Problem with Uncertainty (STPU), a problem is dynamically controllable if there is a successful dynamic strategy such that every decision in it is made according to the observations of past events. In the thesis, we make the following contributions. (1) We introduce an optimisation model for STPU based on the existing dynamic controllability checking algorithms. Some flexibility and robustness measures are introduced based on the model. (2) We extend the definition and verification algorithm of dynamic controllability to temporal problems with controllable discrete variables and uncertainty, which is called Controllable Conditional Temporal Problems with Uncertainty (CCTPU). An entirely dynamically controllable strategy of CCTPU consists of both temporal scheduling and variable assignments being dynamically decided, which maximize the flexibility of the execution. (3) We introduce optimisation models of CCTPU under fully dynamic controllability. The optimisation models aim to answer the questions how flexible, robust or controllable a schedule or temporal plan is. The experiments show that making decisions dynamically can achieve better objective values than doing statically. The thesis also contributes to the field of AI planning and scheduling by introducing robustness metrics of temporal networks, proposing an envelope-based algorithm that can check dynamic controllability of temporal networks with uncertainty and controllable discrete decisions, evaluating improvements from making decisions strongly controllable to temporally dynamically controllable and fully dynamically controllable and comparing the runtime of different implementations to present the scalability of dynamically controllable strategies

Group Decision Making and Temporal Reasoning

The more capable and autonomous computer systems become, the more important it is for them to be able to act collaboratively, whether in groups consisting solely of other computers or in heterogeneous groups of computers and people. To act collaboratively requires that systems have effective group decision-making capabilities. This thesis makes four important contributions to the design of group decision-making mechanisms and algorithms for deploying them in collaborative, multi-agent systems. First, it provides an abstract framework for the specification of group decision-making mechanisms that computer agents can use to coordinate their planning activity when collaborating with other agents. Second, it specifies a combinatorial auction-based mechanism that computer agents can use to help them decide, both individually and collectively, whether to engage in a collaborative activity. Third, it extends the theory of Simple Temporal Networks by providing a rigorous theoretical analysis of an important family of temporal reasoning problems. Fourth, it provides sound, complete and polynomial-time algorithms for solving those temporal reasoning problems and specifies the use of such algorithms by agents participating in the auction-based mechanism.Engineering and Applied Science

Multi-Agent Systems

A multi-agent system (MAS) is a system composed of multiple interacting intelligent agents. Multi-agent systems can be used to solve problems which are difficult or impossible for an individual agent or monolithic system to solve. Agent systems are open and extensible systems that allow for the deployment of autonomous and proactive software components. Multi-agent systems have been brought up and used in several application domains

Managing temporal uncertainty under limited communication : a formal model of tight and loose team coordination

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2004.Includes bibliographical references (leaves 155-157).In the future, groups of autonomous robots will cooperate in large networks in order to achieve a common goal. These multi-agent systems will need to be able to execute cooperative temporal plans in the presence of temporal uncertainty and communication limitations. The duration of many planned activities will not be under direct control of the robots. In addition, robots will often not be able to communicate during plan execution. In order for the robots to robustly execute a cooperative plan, they will need to guarantee that a successful execution strategy exists, and provide a means to reactively compensate for the uncertainty in real-time. This thesis presents a multi-agent executive that enables groups of distributed autonomous robots to dynamically schedule temporally flexible plans that contain both temporal uncertainty under communication limitations. Previous work has presented controllability algorithms that compile the simple temporal networks with uncertainty, STNUs, into a form suitable for execution. This thesis extends the previous controllability algorithms to operate on two-layer plans that specify group level coordination at the highest level and agent level coordination at a lower level. We introduce a Hierarchical Reformulation (HR) algorithm that reformulates the two-layer plan in order to enable agents to dynamically adapt to uncertainty within each group plan and use a static execution strategy between groups in order to compensate for communication limitations. Formally, the HR algorithm ensures that the two-layer plan is strongly controllable at the highest level and dynamically controllable at the lower level. Furthermore, we introduce a new fast dynamic controllability algorithm that has been empirically shown to run in O(N³)(cont.) The Hierarchical Reformulation algorithm has been validated on a set of hand coded examples. The speed of the new fast dynamic controllability algorithm has been tested using a set of randomly generated problems.by John L. Stedl.S.M

Bringing social reality to multiagent and service architectures : practical reductions for monitoring of deontic-logic and constitutive norms

As distributed systems grow in complexity, the interactions among individuals (agents, services) of such systems become increasingly more complex and therefore more difficult to constrain and monitor. We propose to view such systems as socio-technical systems, in which organisational and institutional concepts, such as norms, can be applied to improve not only control on the components but also their autonomy by the definition of soft rather than hard constraints. Norms can be described as rules that guide the behavior of individual agents pertaining to groups that abide to them, either by explicit or implicit support. The study of norms, and regulatory systems in general, in their many forms -e.g. social norms, conventions, laws, regulations- has been of interest since the beginning of philosophy, but has seen a lot of evolution during the 20th century due to the progress in the philosophy of language, especially concerning speech acts and deontic logic. Although there is a myriad of definitions and related terminologies about the concept of norm, and as such there are many perspectives on how to analyse their impact, a common denominator is that norms constrain the behaviour of groups of agents in a way that each individual agent can build, with a fair degree of confidence, expectations on how each of their counterparts will behave in the situations that the norms are meant to cover. For example, on a road each driver expects everybody else to drive on only one side of the road (right or left, depending on the country). Therefore, normative contexts, usually wrapped in the form of institutions, are effective mechanisms to ensure the stability of a complex system such as an organisation, a society, or even of electronic systems. The latter has been an object of interest in the field of Artificial Intelligence, and it has been seen as a paradigm of coordination among electronic agents either in multi-agent systems or in service-oriented architectures. In order to apply norms to electronic systems, research has come up with abstractions of normative systems. In some cases these abstractions are based on regimented systems with flexible definitions of the notion of norm, in order to include meanings of the concept with a coarse-grained level of logic formality such as conventions. Other approaches, on the other hand, propose the use of deontic logic for describing, from a more theoretical perspective, norm-governed interaction environments. In both cases, the purpose is to enable the monitoring and enforcement of norms on systems that include -although not limited to- electronic agents. In the present dissertation we will focus on the latter type, focusing on preserving the deontic aspect of norms. Monitoring in norm-governed systems requires making agents aware of: 1) what their normative context is, i.e. which obligations, permissions and prohibitions are applicable to each of them and how they are updated and triggered; and 2) what their current normative status is, i.e. which norms are active, and in what instances they are being fullfilled or violated, in order words, what their social -institutional- reality is. The current challenge is on designing systems that allow computational components to infer both the normative context and social reality in real-time, based on a theoretical formalism that makes such inferences sound and correct from a philosophical perspective. In the scope of multi-agent systems, many are the approaches proposed and implemented that full these requirements up to this date. However, the literature is still lacking a proposal that is suited to the current state-of-the-art in service-oriented architectures, more focused nowadays on automatically scalable, polyglot amalgams of lightweight services with extremely simple communication and coordination mechanisms- a trend that is being called “microservices”. This dissertation tackles this issue, by 1) studying what properties we can infer from distributed systems that allow us to treat them as part of a socio-technical system, and 2) analysing which mechanisms we can provide to distributed systems so that they can properly act as socio-technical systems. The main product of the thesis is therefore a collection of computational elements required for formally grounded and real-time e¬fficient understanding and monitoring of normative contexts, more specially: 1. An ontology of events to properly model the inputs from the external world and convert them into brute facts or institutional events; 2. A lightweight language for norms, suitable for its use in distributed systems; 3. An especially tailored formalism for the detection of social reality, based on and reducible to deontic logic with support for constitutive norms; 4. A reduction of such formalism to production rule systems; and 5. One or more implementations of this reduction, proven to e¬fficiently work on several scenarios. This document presents the related work, the rationale and the design/implementation of each one of these elements. By combining them, we are able to present novel, relevant work that enables the application of normative reasoning mechanisms in realworld systems in the form of a practical reasoner. Of special relevance is the fact that the work presented in this dissertation simplifies, while preserving formal soundness, theoretically complex forms of reasoning. Nonetheless, the use of production systems as the implementation-level materialisation of normative monitoring allows our work to be applied in any language and/or platform available, either in the form of rule engines, ECA rules or even if-then-else patterns. The work presented has been tested and successfully used in a wide range of domains and actual applications. The thesis also describes how our mechanisms have been applied to practical use cases based on their integration into distributed eldercare management and to commercial games.Con el incremento en la complejidad de los sistemas distribuidos, las interacciones entre los individuos (agentes, servicios) de dichos sistemas se vuelven más y más complejas y, por ello, más difíciles de restringir y monitorizar. Proponemos ver a estos sistemas como sistemas socio-técnicos, en los que conceptos organizacionales e institucionales (como las normas) pueden aplicarse para mejorar no solo el control sobre los componentes sino también su autonomía mediante la definición de restricciones débiles (en vez de fuertes). Las Normas se pueden describir como reglas que guían el comportamiento de agentes individuales que pertenecen a grupos que las siguen, ya sea con un apoyo explícito o implícito. El estudio de las normas y de los sistemas regulatorios en general y en sus formas diversas -normas sociales, convenciones, leyes, reglamentos- ha sido de interés para los eruditos desde los inicios de la filosofía, pero ha sufrido una evolución mayor durante el siglo 20 debido a los avances en filosofía del lenguaje, en especial los relacionados con los actos del habla -speech acts en inglés- y formas deónticas de la lógica modal. Aunque hay una gran variedad de definiciones y terminología asociadas al concepto de norma, y por ello existen varios puntos de vista sobre como analizar su impacto, el denominador común es que las normas restringen el comportamiento de grupos de agentes de forma que cada agente individual puede construir, con un buen nivel de confianza, expectativas sobre cómo cada uno de los otros actores se comportará en las situaciones que las normas han de cubrir. Por ejemplo, en una carretera cada conductor espera que los demás conduzcan solo en un lado de la carretera (derecha o izquierda, dependiendo del país). Por lo tanto, los contextos normativos, normalmente envueltos en la forma de instituciones, constituyen mecanismos efectivos para asegurar la estabilidad de un sistema complejo como una organización, una sociedad o incluso un sistema electrónico. Lo último ha sido objeto de estudio en el campo de la Inteligencia Artificial, y se ha visto como paradigma de coordinación entre agentes electrónicos, tanto en sistemas multiagentes como en arquitecturas orientadas a servicios. Para aplicar normas en sistemas electrónicos, los investigadores han creado abstracciones de sistemas normativos. En algunos casos estas abstracciones se basan en sistemas regimentados con definiciones flexibles del concepto de norma para poder influir algunos significados del concepto con un menor nivel de granularidad formal como es el caso de las convenciones. Otras aproximaciones proponen el uso de lógica deóntica para describir, desde un punto de vista más teórico, entornos de interacción gobernados por normas. En ambos casos el propósito es el permitir la monitorización y la aplicación de las normas en sistemas que incluyen -aunque no están limitados a- agentes electrónicos. En el presente documento nos centraremos en el segundo tipo, teniendo cuidado en mantener el aspecto deóntico de las normas. La monitorización en sistemas gobernados por normas requiere el hacer a los agentes conscientes de: 1) cual es su contexto normativo, es decir, que obligaciones permisos y prohibiciones se aplican a cada uno de ellos y cómo se actualizan y activan; y 2) cual es su estado normativo actual, esto es, que normas están activas, y que instancias están siendo cumplidas o violadas, en definitiva, cual es su realidad social -o institucional-. En la actualidad el reto consiste en diseñar sistemas que permiten inferir a componentes computacionales tanto el contexto normativo como la realidad social en tiempo real, basándose en un formalismo teórico que haga que dichas inferencias sean correctas y bien fundamentadas desde el punto de vista filosófico. En el ámbito de los sistemas multiagente existen muchas aproximaciones propuestas e implementadas que cubren estos requisitos. Sin embargo, esta literatura aun carece de una propuesta que sea adecuada para la tecnología de las arquitecturas orientadas a servicios, que están más centradas en amalgamas políglotas y escalables de servicios ligeros con mecanismos de coordinación y comunicación extremadamente simples, una tendencia moderna que lleva el nombre de microservicios. Esta tesis aborda esta problemática 1) estudiando que propiedades podemos inferir de los sistemas distribuidos que nos permitan tratarlos como parte de un sistema sociotécnico, y 2) analizando que mecanismos podemos proporcionar a los sistemas distribuidos de forma que puedan actuar de forma correcta como sistemas socio-técnicos. El producto principal de la tesis es, por tanto, una colección de elementos computacionales requeridos para la monitorización e interpretación e_cientes en tiempo real y con clara base formal. En concreto: 1. Una ontología de eventos para modelar adecuadamente las entradas del mundo exterior y convertirlas en hechos básicos o en eventos institucionales; 2. Un lenguaje de normas ligero y sencillo, adecuado para su uso en arquitecturas orientadas a servicios; 3. Un formalismo especialmente adaptado para la detección de la realidad social, basado en y reducible a lógica deóntica con soporte para normas constitutivas; 4. Una reducción de ese formalismo a sistemas de reglas de producción; y 5. Una o más implementaciones de esta reducción, de las que se ha probado que funcionan eficientemente en distintos escenarios. Este documento presenta el estado del arte relacionado, la justificación y el diseño/implementación para cada uno de esos elementos. Al combinarlos, somos capaces de presentar trabajo novedoso y relevante que permite la aplicación de mecanismos de razonamiento normativo en sistemas del mundo real bajo la forma de un razonador práctico. De especial relevancia es el hecho de que el trabajo presentado en este documento simplifica formas complejas y teóricas de razonamiento preservando la correctitud formal. El uso de sistemas de reglas de producción como la materialización a nivel de implementación del monitoreo normativo permite que nuestro trabajo se pueda aplicar a cualquier lenguaje o plataforma disponible, ya sea en la forma de motores de reglas, reglas ECA o incluso patrones si-entonces. El trabajo presentado ha sido probado y usado con éxito en un amplio rango de dominios y aplicaciones prácticas. La tesis describe como nuestros mecanismos se han aplicado a casos prácticos de uso basados en su integración en la gestión distribuida de pacientes de edad avanzada o en el sector de los videojuegos comerciales.Postprint (published version

Robust, goal-directed plan execution with bounded risk

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 273-283).There is an increasing need for robust optimal plan execution for multi-agent systems in uncertain environments, while guaranteeing an acceptable probability of success. For example, a fleet of unmanned aerial vehicles (UAVs) and autonomous underwater vehicles (AUVs) are required to operate autonomously for an extensive mission duration in an uncertain environment. Previous work introduced the concept of a model-based executive, which increases the level of autonomy, elevating the level at which systems are commanded. This thesis develops model-based executives that reason explicitly from a stochastic plant model to find the optimal course of action, while ensuring that the probability of failure is within a user-specified risk bound. This thesis presents two robust mode-based executives: probabilistic Sulu or p-Sulu, and distributed probabilistic Sulu or dp-Sulu. The objective for p-Sulu and dp-Sulu is to allow users to command continuous, stochastic multi-agent systems in a manner that is both intuitive and safe. The user specifies the desired evolution of the plant state, as well as the acceptable probabilities of failure, as a temporal plan on states called a chance-constrained qualitative state plan (CCQSP). An example of a CCQSP statement is "go to A through B within 30 minutes, with less than 0.001% probability of failure." p-Sulu and dp-Sulu take a CCQSP, a continuous plant model with stochastic uncertainty, and an objective function as inputs, and outputs an optimal continuous control sequence, as well as an optimal discrete schedule. The difference between p-Sulu and dp-Sulu is that p-Sulu plans in a centralized manner while dp-Sulu plans in a distributed manner. dp-Sulu enables robust CCQSP execution for multi-agent systems. We solve the problem based on the key concept of risk allocation, which achieves tractability by allocating the specified risk to individual constraints and mapping the result into an equivalent deterministic constrained optimization problem. Risk allocation also enables a distributed plan execution for multi-agent systems by distributing the risk among agents to decompose the optimization problem. Building upon the risk allocation approach, we develop our first CCQSP executive, p-Sulu, in four spirals. First, we develop the Convex Risk Allocation (CRA) algorithm, which can solve a CCQSP planning problem with a convex state space and a fixed schedule, highlighting the capability of optimally allocating risk to individual constraints. Second, we develop the Non-convex Iterative Risk Allocation (NIRA) algorithm, which can handle non-convex state space. Third, we build upon NIRA a full-horizon CCQSP planner, p-Sulu FH, which can optimize not only the control sequence but also the schedule. Fourth, we develop p-Sulu, which enables the real-time execution of CCQSPs by employing the receding horizon approach. Our second CCQSP executive, dp-Sulu, is developed in two spirals. First, we develop the Market-based Iterative Risk Allocation (MIRA) algorithm, which can control a multiagent system in a distributed manner by optimally distributing risk among agents through the market-based method called tatonnement. Second and finally, we integrate the capability of MIRA into p-Sulu to build the robust model-based executive, dp-Sulu, which can execute CCQSPs on multi-agent systems in a distributed manner. Our simulation results demonstrate that our executives can efficiently execute CCQSP planning problems with significantly reduced suboptimality compared to prior art.by Masahiro Ono.Ph.D