Towards formal models and languages for verifiable Multi-Robot Systems

Incorrect operations of a Multi-Robot System (MRS) may not only lead to unsatisfactory results, but can also cause economic losses and threats to safety. These threats may not always be apparent, since they may arise as unforeseen consequences of the interactions between elements of the system. This call for tools and techniques that can help in providing guarantees about MRSs behaviour. We think that, whenever possible, these guarantees should be backed up by formal proofs to complement traditional approaches based on testing and simulation. We believe that tailored linguistic support to specify MRSs is a major step towards this goal. In particular, reducing the gap between typical features of an MRS and the level of abstraction of the linguistic primitives would simplify both the specification of these systems and the verification of their properties. In this work, we review different agent-oriented languages and their features; we then consider a selection of case studies of interest and implement them useing the surveyed languages. We also evaluate and compare effectiveness of the proposed solution, considering, in particular, easiness of expressing non-trivial behaviour.Comment: Changed formattin

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

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 zugänglich.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

An agent-based traffic simulation framework to model intelligent virtual driver behaviour

This paper presents an agent-based traffic simulation framework that supports intelligent virtual driver behaviour. The framework exploits concepts used in Artificial Life (ALife), Artificial Intelligence (AI) and Agent technology to model the inherent unpredictability and autonomous behaviour of drivers within traffic simulation models. Each driver agent in our system contains knowledge and a decision-making mechanism, both of which are based on heuristics. This approach replaces some of the prescriptive nature of driving simulation models by allowing behaviours to emerge as a result of individual driver agent interactions. The framework also contributes to accident analysis by improving current limitations in which accident investigation methods concentrate on the events themselves, rather than pre-crash influences. Within this context, the framework provides an opportunity to increase the understanding of accident causation factors, to examine alternative traffic scenarios (what if analyses) and methodology to obtain quantitative estimates of accident risk. Current implementation results show that driver agents within the integrated simulation are able to perceive other drivers’ speeds and distances, avoid collisions, perform realistic vehicle following, and demonstrate emergent traffic flow. A major application area for this framework includes the evaluation of vehicle, highway and road user factors that precede a collision, or near misses

INTEROPERABILITY FOR MODELING AND SIMULATION IN MARITIME EXTENDED FRAMEWORK

This thesis reports on the most relevant researches performed during the years of the Ph.D. at the Genova University and within the Simulation Team. The researches have been performed according to M&S well known recognized standards. The studies performed on interoperable simulation cover all the environments of the Extended Maritime Framework, namely Sea Surface, Underwater, Air, Coast & Land, Space and Cyber Space. The applications cover both the civil and defence domain. The aim is to demonstrate the potential of M&S applications for the Extended Maritime Framework, applied to innovative unmanned vehicles as well as to traditional assets, human personnel included. A variety of techniques and methodology have been fruitfully applied in the researches, ranging from interoperable simulation, discrete event simulation, stochastic simulation, artificial intelligence, decision support system and even human behaviour modelling

Towards Verifiably Ethical Robot Behaviour

Ensuring that autonomous systems work ethically is both complex and difficult. However, the idea of having an additional `governor' that assesses options the system has, and prunes them to select the most ethical choices is well understood. Recent work has produced such a governor consisting of a `consequence engine' that assesses the likely future outcomes of actions then applies a Safety/Ethical logic to select actions. Although this is appealing, it is impossible to be certain that the most ethical options are actually taken. In this paper we extend and apply a well-known agent verification approach to our consequence engine, allowing us to verify the correctness of its ethical decision-making.Comment: Presented at the 1st International Workshop on AI and Ethics, Sunday 25th January 2015, Hill Country A, Hyatt Regency Austin. Will appear in the workshop proceedings published by AAA

Human behaviour modelling in complex socio-technical systems : an agent based approach

For many years we have been striving to understand human behaviour and our interactions with our socio-technological environment. By advancing our knowledge in this area, we have helped the design of new or improved work processes and technologies. Historically, much of the work in analysing social interactions has been conducted within the social sciences. However, computer simulation has brought an extra tool in trying to understand and model human behaviours. Using an agent based approach this presentation describes my work in constructing computational models of human behaviour for informing design through simulation. With examples from projects in two main application areas of crisis and emergency management, and energy management I describe how my work addresses some main issues in agent based social simulation. The first concerns the process by which we develop these models. The second lies in the nature of socio-technical systems. Human societies are a perfect example of a complex system exhibiting characteristics of self-organisation, adaptability and showing emergent phenomena such as cooperation and robustness. I describe how complex systems theory may be applied to improve our understanding of socio-technical systems, and how our micro level interactions lead to emergent mutual awareness for problem-solving. From agent based simulation systems I show how context awareness may be modelled. Looking forward to the future, I discuss how the increasing prevalence of artificial agents in our society will cause us to re-examine the new types of interactions and cooperative behaviours that will emerge.Depuis de nombreuses années, nous nous sommes efforcés de comprendre le comportement humain et nos interactions avec l'environnement sociotechnique. Grâce à l'avancée de nos connaissances dans ce domaine, nous avons contribué à la conception de technologies et de processus de travail nouveaux ou améliorés. Historiquement, une part importante du travail d'analyse des interactions sociales fut entreprise au sein des sciences sociales. Cependant, la simulation informatique a apporté un nouvel outil pour tenter de comprendre et de modéliser les comportements humains. En utilisant une approche à base d'agents, cette présentation décrit mon travail sur la construction de modèles informatiques du comportement humain pour guider la conception par la simulation. A l'aide d'exemples issus de projets des deux domaines d'application que sont la gestion des crises et de l'urgence et la gestion de l'énergie, je décris comment mon travail aborde certains problèmes centraux à la simulation sociale à base d'agents. Le premier concerne le processus par lequel nous développons ces modèles. Le second problème provient de la nature des systèmes sociotechniques. Les sociétés humaines constituent un exemple parfait de système complexe possédant des caractéristiques d'auto-organisation et d'adaptabilité, et affichant des phénomènes émergents tels que la coopération et la robustesse. Je décris comment la théorie des systèmes complexes peut être appliquée pour améliorer notre compréhension des systèmes sociotechniques, et comment nos interactions au niveau microscopique mènent à l'émergence d'une conscience mutuelle pour la résolution de problèmes. A partir de systèmes de simulation à base d'agents, je montre comment la conscience du contexte peut être modélisée. En terme de perspectives, j'expliquerai comment la hausse de la prévalence des agents artificiels dans notre société nous forcera à considérer de nouveaux types d'interactions et de comportements coopératifs

A robot swarm assisting a human fire-fighter

Emergencies in industrial warehouses are a major concern for fire-fighters. The large dimensions, together with the development of dense smoke that drastically reduces visibility, represent major challenges. The GUARDIANS robot swarm is designed to assist fire-fighters in searching a large warehouse. In this paper we discuss the technology developed for a swarm of robots assisting fire-fighters. We explain the swarming algorithms that provide the functionality by which the robots react to and follow humans while no communication is required. Next we discuss the wireless communication system, which is a so-called mobile ad-hoc network. The communication network provides also the means to locate the robots and humans. Thus, the robot swarm is able to provide guidance information to the humans. Together with the fire-fighters we explored how the robot swarm should feed information back to the human fire-fighter. We have designed and experimented with interfaces for presenting swarm-based information to human beings