Intelligent agents for lawyers

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Compositional Design and Verification of a Multi-Agent System for One-to-Many Negotiation

A compositional verification method for multi-agent systems is presented and applied to a multi-agent system for one-to-many negotiation in the domain of load balancing of electricity use. Advantages of the method are that the complexity of the verification process is managed by compositionality, and that parts of the proofs can be reused in relation to reuse of components

Agent-based simulation of animal behaviour

In this paper it is shown how animal behaviour can be simulated in an agent-based manner. Different models are shown for different types of behaviour, varying from purely reactive behaviour to pro-active, social and adaptive behaviour. The compositional development method for multi-agent systems DESIRE and its software environment supports the conceptual and detailed design, and execution of these models. Experiments reported in the literature on animal behaviour have been simulated for a number of agent models

City-Friendly Smart Network Technologies and Infrastructures: The Spanish Experience

Efficient, resilient, and sustainable electricity delivery is a key cornerstone in increasingly large and complex urban environments, where citizens expect to keep or rise their living standards. In this context, cost-effective and ubiquitous digital technologies are driving the transformation of existing electrical infrastructures into truly smart systems capable of better providing the services a low-carbon society is demanding. The goal of this paper is twofold: 1) to review the dramatically evolving landscape of power systems, from the old framework based on centralized generation and control, aimed at serving inelastic customers through alternating current (ac) transmission networks and one-way distribution feeders, to a new paradigm centered mainly around two main axes: renewable generation, both centralized and distributed, and active customers (prosumers), interacting with each other through hybrid ac/dc smart grids; 2) to illustrate, through featured success stories, how several smart grid concepts and technologies have been put into practice in Spain over the last few years to optimize the performance of urban electrical assets

Practical strategies for agent-based negotiation in complex environments

Agent-based negotiation, whereby the negotiation is automated by software programs, can be applied to many different negotiation situations, including negotiations between friends, businesses or countries. A key benefit of agent-based negotiation over human negotiation is that it can be used to negotiate effectively in complex negotiation environments, which consist of multiple negotiation issues, time constraints, and multiple unknown opponents. While automated negotiation has been an active area of research in the past twenty years, existing work has a number of limitations. Specifically, most of the existing literature has considered time constraints in terms of the number of rounds of negotiation that take place. In contrast, in this work we consider time constraints which are based on the amount of time that has elapsed. This requires a different approach, since the time spent computing the next action has an effect on the utility of the outcome, whereas the actual number of offers exchanged does not. In addition to these time constraints, in the complex negotiation environments which we consider, there are multiple negotiation issues, and we assume that the opponents’ preferences over these issues and the behaviour of those opponents are unknown. Finally, in our environment there can be concurrent negotiations between many participants.Against this background, in this thesis we present the design of a range of practical negotiation strategies, the most advanced of which uses Gaussian process regression to coordinate its concession against its various opponents, whilst considering the behaviour of those opponents and the time constraints. In more detail, the strategy uses observations of the offers made by each opponent to predict the future concession of that opponent. By considering the discounting factor, it predicts the future time which maximises the utility of the offers, and we then use this in setting our rate of concession.Furthermore, we evaluate the negotiation agents that we have developed, which use our strategies, and show that, particularly in the more challenging scenarios, our most advanced strategy outperforms other state-of-the-art agents from the Automated Negotiating Agent Competition, which provides an international benchmark for this work. In more detail, our results show that, in one-to-one negotiation, in the highly discounted scenarios, our agent reaches outcomes which, on average, are 2.3% higher than those of the next best agent. Furthermore, using empirical game theoretic analysis we show the robustness of our strategy in a variety of tournament settings. This analysis shows that, in the highly discounted scenarios, no agent can benefit by choosing a different strategy (taken from the top four strategies in that setting) than ours. Finally, in the many-to-many negotiations, we show how our strategy is particularly effective in highly competitive scenarios, where it outperforms the state-of-the-art many-to-many negotiation strategy by up to 45%

Development and Specification of Virtual Environments

This thesis concerns the issues involved in the development of virtual environments (VEs). VEs are more than virtual reality. We identify four main characteristics of them: graphical interaction, multimodality, interface agents, and multi-user. These characteristics are illustrated with an overview of different classes of VE-like applications, and a number of state-of-the-art VEs. To further define the topic of research, we propose a general framework for VE systems development, in which we identify five major classes of development tools: methodology, guidelines, design specification, analysis, and development environments. Of each, we give an overview of existing best practices

An adaptive multi-agent system for the distribution of intelligence in electrical distribution networks: state estimation

L'électricité joue un rôle de plus en plus important dans notre société. En effet, nous nous dirigeons vers l'ère du "tout électrique". Les besoins évoluant, il est indispensable de repenser la manière dont l'électricité est produite et distribuée. Cela introduit le concept de Smart Grid. Le Smart Grid est un concept de réseau électrique capable de supporter de manière autonome et intelligente les changements et pannes qui pourraient survenir dans un réseau. Cela répond directement au fait que de part la nature fortement distribuée et l'imprédictibilité de l'environnement (météo, ...), ces événements sont imprévisibles. Pour cela, cette thèse propose un cadre applicatif (framework) innovant basé sur les multi-agents ainsi que la conception et l'implémentation de comportements coopératifs pour résoudre deux problémes courants dans les réseaux électriques: l'analyse des flux de puissance et l'estimation d'état. Ces problèmes ont été abordés avec l'approche des Systèmes Multi-Agent Adaptatifs. Ces systèmes sont efficaces pour résoudre des problèmes complexes et ont la capacité d'adapter leur fonctionnement aux évolutions de leur environnement. Les résultats obtenus indiquent la pertinence d'utiliser de tels systèmes adaptatifs pour résoudre les problèmes inhérents au concept de Smart Grid.Electricity plays an increasingly important role in our society. Indeed, we are moving toward the era of "everything electric". The needs evolving, it is mandatory to rethink the way electricity is produced and distributed. This then introduces the concept of an autonomous and intelligent power system called the Smart Grid. The Smart Grid is a concept of electrical network able to support autonomously any changes and faults that may occur. Obviously, the geographical distribution of electrical networks and the environment (weather conditions, ...) make it impossible to predict events that will occur. To do this, this study proposes an innovative agent-based framework as well as the design and implementation of cooperative agents behaviors aiming at solving common power systems related problems: the Load Flow analysis and the State Estimation. These issues have been addressed by the mean of Adaptive Multi-Agent Systems. These systems are known to be efficient to solve complex problems and have the ability to adapt their functioning to the evolutions of their environment. The results obtained show the relevance of using such self-adaptive systems to solve the issues inherent to the Smart Grid

Practical strategies for agent-based negotiation in complex environments

Agent-based negotiation, whereby the negotiation is automated by software programs, can be applied to many different negotiation situations, including negotiations between friends, businesses or countries. A key benefit of agent-based negotiation over human negotiation is that it can be used to negotiate effectively in complex negotiation environments, which consist of multiple negotiation issues, time constraints, and multiple unknown opponents. While automated negotiation has been an active area of research in the past twenty years, existing work has a number of limitations. Specifically, most of the existing literature has considered time constraints in terms of the number of rounds of negotiation that take place. In contrast, in this work we consider time constraints which are based on the amount of time that has elapsed. This requires a different approach, since the time spent computing the next action has an effect on the utility of the outcome, whereas the actual number of offers exchanged does not. In addition to these time constraints, in the complex negotiation environments which we consider, there are multiple negotiation issues, and we assume that the opponents’ preferences over these issues and the behaviour of those opponents are unknown. Finally, in our environment there can be concurrent negotiations between many participants. Against this background, in this thesis we present the design of a range of practical negotiation strategies, the most advanced of which uses Gaussian process regression to coordinate its concession against its various opponents, whilst considering the behaviour of those opponents and the time constraints. In more detail, the strategy uses observations of the offers made by each opponent to predict the future concession of that opponent. By considering the discounting factor, it predicts the future time which maximises the utility of the offers, and we then use this in setting our rate of concession. Furthermore, we evaluate the negotiation agents that we have developed, which use our strategies, and show that, particularly in the more challenging scenarios, our most advanced strategy outperforms other state-of-the-art agents from the Automated Negotiating Agent Competition, which provides an international benchmark for this work. In more detail, our results show that, in one-to-one negotiation, in the highly discounted scenarios, our agent reaches outcomes which, on average, are 2.3% higher than those of the next best agent. Furthermore, using empirical game theoretic analysis we show the robustness of our strategy in a variety of tournament settings. This analysis shows that, in the highly discounted scenarios, no agent can benefit by choosing a different strategy (taken from the top four strategies in that setting) than ours. Finally, in the many-to-many negotiations, we show how our strategy is particularly effective in highly competitive scenarios, where it outperforms the state-of-the-art many-to-many negotiation strategy by up to 45%.EThOS - Electronic Theses Online ServiceGBUnited Kingdo