Creating agent platforms to host agent-mediated services that share resources

After a period where the Internet was exclusively filled with content, the present efforts are moving towards services, which handle the raw information to create value from it. Therefore labors to create a wide collection of agent-based services are being perfomed in several projects, such as Agentcities does. In this work we present an architecture for agent platforms named a-Buildings. The aim of the proposed architecture is to ease the creation, installation, search and management of agent-mediated services and the share of resources among services. To do so the a-Buildings architecture creates a new level of abstraction on top of the standard FIPA agent platform specification. Basically, an a-Building is a service-oriented platform which offers a set of low level services to the agents it hosts. We define low level services as those required services that are neccesary to create more complex high level composed services.Postprint (published version

The ‘frustrated’ housing aspirations of generation rent

No abstract available

Accumulation Regimes in Dynastic Economies with Resource Dependence and Habit Formation

We analyze the consequences of habit formation for income levels and long-term growth in an overlapping generations model with dynastic altruism and resource dependence. If the strength of habits is below a critical level, the competitive economy displays an altruistic (Ramsey-like) equilibrium where consumption sustainability obeys the Stiglitz condition, and habits yield permanent effects on output levels due to transitional effects on growth rates, capital profitability and speed of resource depletion. If the strength of habits is above the critical threshold, the economy achieves a selfish (Diamond-like) equilibrium in which habits increase growth rates and resource depletion even in the long run, sustainability conditions are less restrictive, consumption and output grow faster than in Ramsey equilibria, but welfare is much lower. Results hinge on resource dependence, as different depletion rates modify the intergenerational distribution of wealth and thereby the growth rate attained in either equilibrium.Dynastic Altruism, Overlapping Generations, Capital-Resource Model, Habit Formation

Commercial software tools for intelligent autonomous systems

This article identifies some of the commercial software tools that can potentially be examined, or relied upon for their techniques, within new EPSRC projects entitled "Reconfigurable Autonomy" and "Distributed Sensing and Control.." awarded and to be undertaken between Liverpool, Southampton and Surrey Universities in the next 4 years. Although such projects strive to produce new techniques of various kinds, the software reviewed here could also influence, shape and help to integrate the algorithmic outcome of all 16 projects awarded within the EPSRC Autonomous and Intelligent Systems programme early 2012. To avoid mis-representation of technololgies provided by the software producer companies listed, most of this review is based on using quotes from original product descriptions

An Expressive Language and Efficient Execution System for Software Agents

Software agents can be used to automate many of the tedious, time-consuming information processing tasks that humans currently have to complete manually. However, to do so, agent plans must be capable of representing the myriad of actions and control flows required to perform those tasks. In addition, since these tasks can require integrating multiple sources of remote information ? typically, a slow, I/O-bound process ? it is desirable to make execution as efficient as possible. To address both of these needs, we present a flexible software agent plan language and a highly parallel execution system that enable the efficient execution of expressive agent plans. The plan language allows complex tasks to be more easily expressed by providing a variety of operators for flexibly processing the data as well as supporting subplans (for modularity) and recursion (for indeterminate looping). The executor is based on a streaming dataflow model of execution to maximize the amount of operator and data parallelism possible at runtime. We have implemented both the language and executor in a system called THESEUS. Our results from testing THESEUS show that streaming dataflow execution can yield significant speedups over both traditional serial (von Neumann) as well as non-streaming dataflow-style execution that existing software and robot agent execution systems currently support. In addition, we show how plans written in the language we present can represent certain types of subtasks that cannot be accomplished using the languages supported by network query engines. Finally, we demonstrate that the increased expressivity of our plan language does not hamper performance; specifically, we show how data can be integrated from multiple remote sources just as efficiently using our architecture as is possible with a state-of-the-art streaming-dataflow network query engine

Probabilistic Guarantees for Safe Deep Reinforcement Learning

Deep reinforcement learning has been successfully applied to many control tasks, but the application of such agents in safety-critical scenarios has been limited due to safety concerns. Rigorous testing of these controllers is challenging, particularly when they operate in probabilistic environments due to, for example, hardware faults or noisy sensors. We propose MOSAIC, an algorithm for measuring the safety of deep reinforcement learning agents in stochastic settings. Our approach is based on the iterative construction of a formal abstraction of a controller's execution in an environment, and leverages probabilistic model checking of Markov decision processes to produce probabilistic guarantees on safe behaviour over a finite time horizon. It produces bounds on the probability of safe operation of the controller for different initial configurations and identifies regions where correct behaviour can be guaranteed. We implement and evaluate our approach on agents trained for several benchmark control problems

Social influence, negotiation and cognition

To understand how personal agreements can be generated within complexly differentiated social systems, we develop an agent-based computational model of negotiation in which social influence plays a key role in the attainment of social and cognitive integration. The model reflects a view of social influence that is predicated on the interactions among such factors as the agents' cognition, their abilities to initiate and maintain social behaviour, as well as the structural patterns of social relations in which influence unfolds. Findings from a set of computer simulations of the model show that the degree to which agents are influenced depends on the network of relations in which they are located, on the order in which interactions occur, and on the type of information that these interactions convey. We also find that a fundamental role in explaining influence is played by how inclined the agents are to be concilatory with each other, how accurate their beliefs are, and how self-confident they are in dealing with their social interactions. Moreover, the model provides insights into the trade-offs typically involved in the exercise of social influence

A distributed agent architecture for real-time knowledge-based systems: Real-time expert systems project, phase 1

We propose a distributed agent architecture (DAA) that can support a variety of paradigms based on both traditional real-time computing and artificial intelligence. DAA consists of distributed agents that are classified into two categories: reactive and cognitive. Reactive agents can be implemented directly in Ada to meet hard real-time requirements and be deployed on on-board embedded processors. A traditional real-time computing methodology under consideration is the rate monotonic theory that can guarantee schedulability based on analytical methods. AI techniques under consideration for reactive agents are approximate or anytime reasoning that can be implemented using Bayesian belief networks as in Guardian. Cognitive agents are traditional expert systems that can be implemented in ART-Ada to meet soft real-time requirements. During the initial design of cognitive agents, it is critical to consider the migration path that would allow initial deployment on ground-based workstations with eventual deployment on on-board processors. ART-Ada technology enables this migration while Lisp-based technologies make it difficult if not impossible. In addition to reactive and cognitive agents, a meta-level agent would be needed to coordinate multiple agents and to provide meta-level control

Potential of PM-selected components to induce oxidative stress and root system alteration in a plant model organism

Over the last years, various acellular assays have been used for the evaluation of the oxidative potential (OP) of particular matter (PM) to predict PM capacity to generate reactive oxygen (ROS) and nitrogen (RNS) species in biological systems. However, relationships among OP and PM toxicological effects on living organisms are still largely unknown. This study aims to assess the effects of atmospheric PM-selected components (brake dust - BD, pellet ash - PA, road dust - RD, certified urban dust NIST1648a - NIST, soil dust - S, coke dust - C and Saharan dust - SD) on the model plant A. thaliana development, with emphasis on their capacity to induce oxidative stress and root morphology alteration. Before growing A. thaliana in the presence of the PM-selected components, each atmospheric dust has been chemically characterized and tested for the OP through dithiothreitol (DTT), ascorbic acid (AA) and 2′,7′-dichlorofluorescin (DCFH) assays. After the exposure, element bioaccumulation in the A. thaliana seedlings, i.e., in roots and shoots, was determined and both morphological and oxidative stress analyses were performed in roots. The results indicated that, except for SD and S, all the tested dusts affected A. thaliana root system morphology, with the strongest effects in the presence of the highest OPs dusts (BD, PA and NIST). Principal component analysis (PCA) revealed correlations among OPs of the dusts, element bioaccumulation and root morphology alteration, identifying the most responsible dust-associated elements affecting the plant. Lastly, histochemical analyses of NO and O2•− content and distribution confirmed that BD, PA and NIST induce oxidative stress in A. thaliana, reflecting the high OPs of these dusts and ultimately leading to cell membrane lipid peroxidation