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State Transition Graphs for Semantic Analysis of Movement Behaviours
A behaviour can be defined as a sequence of states or activities occurring one after another. A behaviour consisting of a finite number of reoccurring states/activities may be represented by a directed weighted graph with nodes and edges corresponding, respectively, to the possible states and transitions between them, while the weights represent the probabilities or frequencies of the state and transition occurrences. The same applies to multiple behaviours sharing the same set of possible states. In analysis of movement data, state transition graphs can be used to represent semantic abstractions of mobility behaviours, where states correspond to semantic categories of visited places (such as âhomeâ, âworkâ, âshopâ), activities of moving objects (âdrivingâ, âwalkingâ, âexercisingâ, etc.) or characteristics of the movement (âstraight movementâ, âsharp turnâ, âaccelerationâ, âstopâ, etc.). Such a representation supports the exploration and analysis of the semantic aspect (i.e. the meaning or purposes) of movement. For comprehensive analysis of movement data, state transition graphs need to be combined with representations reflecting the spatial and temporal aspects of the movement. This requires appropriate coordination between different visual displays (graphs, maps and temporal views) and appropriate reaction to analytical operations applied to any of the representations of the same data. We define in an abstract way the reactions of a graph display to analytical operations of querying, partitioning and direct selection. We also propose visual and interactive display features supporting comparisons between data subsets and between results of different operations. We demonstrate the use of the display features by examples of real-world and synthetic data sets
Qualitative design and implementation of human-robot spatial interactions
Despite the large number of navigation algorithms available for mobile robots, in many social contexts they often exhibit inopportune motion behaviours in proximity of people, often with very "unnatural" movements due to the execution of segmented trajectories or the sudden activation of safety mechanisms (e.g., for obstacle avoidance). We argue that the reason of the problem is not only the difficulty of modelling human behaviours and generating opportune robot control policies, but also the way human-robot spatial interactions are represented and implemented.
In this paper we propose a new methodology based on a qualitative representation of spatial interactions, which is both flexible and compact, adopting the well-defined and coherent formalization of Qualitative Trajectory Calculus (QTC). We show the potential of a QTC-based approach to abstract and design complex robot behaviours, where the desired robot's behaviour is represented together with its actual performance in one coherent approach, focusing on spatial interactions rather than pure navigation problems
Agents for educational games and simulations
This book consists mainly of revised papers that were presented at the Agents for Educational Games and Simulation (AEGS) workshop held on May 2, 2011, as part of the Autonomous Agents and MultiAgent Systems (AAMAS) conference in Taipei, Taiwan. The 12 full papers presented were carefully reviewed and selected from various submissions. The papers are organized topical sections on middleware applications, dialogues and learning, adaption and convergence, and agent applications
Automated generation of geometrically-precise and semantically-informed virtual geographic environnements populated with spatially-reasoning agents
La GĂ©o-Simulation Multi-Agent (GSMA) est un paradigme de modĂ©lisation et de simulation de phĂ©nomĂšnes dynamiques dans une variĂ©tĂ© de domaines d'applications tels que le domaine du transport, le domaine des tĂ©lĂ©communications, le domaine environnemental, etc. La GSMA est utilisĂ©e pour Ă©tudier et analyser des phĂ©nomĂšnes qui mettent en jeu un grand nombre d'acteurs simulĂ©s (implĂ©mentĂ©s par des agents) qui Ă©voluent et interagissent avec une reprĂ©sentation explicite de l'espace qu'on appelle Environnement GĂ©ographique Virtuel (EGV). Afin de pouvoir interagir avec son environnement gĂ©ographique qui peut ĂȘtre dynamique, complexe et Ă©tendu (Ă grande Ă©chelle), un agent doit d'abord disposer d'une reprĂ©sentation dĂ©taillĂ©e de ce dernier. Les EGV classiques se limitent gĂ©nĂ©ralement Ă une reprĂ©sentation gĂ©omĂ©trique du monde rĂ©el laissant de cĂŽtĂ© les informations topologiques et sĂ©mantiques qui le caractĂ©risent. Ceci a pour consĂ©quence d'une part de produire des simulations multi-agents non plausibles, et, d'autre part, de rĂ©duire les capacitĂ©s de raisonnement spatial des agents situĂ©s. La planification de chemin est un exemple typique de raisonnement spatial dont un agent pourrait avoir besoin dans une GSMA. Les approches classiques de planification de chemin se limitent Ă calculer un chemin qui lie deux positions situĂ©es dans l'espace et qui soit sans obstacle. Ces approches ne prennent pas en compte les caractĂ©ristiques de l'environnement (topologiques et sĂ©mantiques), ni celles des agents (types et capacitĂ©s). Les agents situĂ©s ne possĂšdent donc pas de moyens leur permettant d'acquĂ©rir les connaissances nĂ©cessaires sur l'environnement virtuel pour pouvoir prendre une dĂ©cision spatiale informĂ©e. Pour rĂ©pondre Ă ces limites, nous proposons une nouvelle approche pour gĂ©nĂ©rer automatiquement des Environnements GĂ©ographiques Virtuels InformĂ©s (EGVI) en utilisant les donnĂ©es fournies par les SystĂšmes d'Information GĂ©ographique (SIG) enrichies par des informations sĂ©mantiques pour produire des GSMA prĂ©cises et plus rĂ©alistes. De plus, nous prĂ©sentons un algorithme de planification hiĂ©rarchique de chemin qui tire avantage de la description enrichie et optimisĂ©e de l'EGVI pour fournir aux agents un chemin qui tient compte Ă la fois des caractĂ©ristiques de leur environnement virtuel et de leurs types et capacitĂ©s. Finalement, nous proposons une approche pour la gestion des connaissances sur l'environnement virtuel qui vise Ă supporter la prise de dĂ©cision informĂ©e et le raisonnement spatial des agents situĂ©s
OCL Plus:Processes and Events in Object-Centred Planning
An important area in AI Planning is the expressiveness of planning domain
specification languages such as PDDL, and their aptitude for modelling real
applications. This paper presents OCLplus, an extension of a hierarchical object
centred planning domain definition language, intended to support the representation
of domains with continuous change. The main extension in OCLplus provides
the capability of interconnection between the planners and the changes that are
caused by other objects of the world. To this extent, the concept of event and process
are introduced in the Hierarchical Task Network (HTN), object centred planning
framework in which a process is responsible for either continuous or discrete
changes, and an event is triggered if its precondition is met. We evaluate the use of
OCLplus and compare it with a similar language, PDDL+
Towards adaptive multi-robot systems: self-organization and self-adaptation
Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugÀnglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.The development of complex systems ensembles that operate in uncertain environments is a major challenge. The reason for this is that system designers are not able to fully specify the system during specification and development and before it is being deployed. Natural swarm systems enjoy similar characteristics, yet, being self-adaptive and being able to self-organize, these systems show beneficial emergent behaviour. Similar concepts can be extremely helpful for artificial systems, especially when it comes to multi-robot scenarios, which require such solution in order to be applicable to highly uncertain real world application. In this article, we present a comprehensive overview over state-of-the-art solutions in emergent systems, self-organization, self-adaptation, and robotics. We discuss these approaches in the light of a framework for multi-robot systems and identify similarities, differences missing links and open gaps that have to be addressed in order to make this framework possible
Analysing Flow Security Properties in Virtualised Computing Systems
This paper studies the problem of reasoning about flow security properties in
virtualised computing networks with mobility from perspective of formal
language. We propose a distributed process algebra CSP_{4v} with security
labelled processes for the purpose of formal modelling of virtualised computing
systems. Specifically, information leakage can come from observations on
process executions, communications and from cache side channels in the
virtualised environment. We describe a cache flow policy to identify such
flows. A type system of the language is presented to enforce the flow policy
and control the leakage introduced by observing behaviours of communicating
processes and behaviours of virtual machine (VM) instances during accessing
shared memory cache
On Formal Methods for Collective Adaptive System Engineering. {Scalable Approximated, Spatial} Analysis Techniques. Extended Abstract
In this extended abstract a view on the role of Formal Methods in System
Engineering is briefly presented. Then two examples of useful analysis
techniques based on solid mathematical theories are discussed as well as the
software tools which have been built for supporting such techniques. The first
technique is Scalable Approximated Population DTMC Model-checking. The second
one is Spatial Model-checking for Closure Spaces. Both techniques have been
developed in the context of the EU funded project QUANTICOL.Comment: In Proceedings FORECAST 2016, arXiv:1607.0200
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