30,482 research outputs found
Median carbon allocation proposal
No full textThis archived document is maintained by the Oregon State Library as part of the Oregon Documents Depository Program. It is for informational purposes and may not be suitable for legal purposes.Title from PDF caption (viewed on Feb. 8, 2007)"December 15, 2006."Mode of access: Internet from the Oregon Government Publications Collection
Task allocation in dynamic networks of satellites
No full textThe management of distributed satellite systems requires the coordination of a large number of heterogeneous spacecraft. Task allocation in such a system is complicated by limited communication and individual satellite dynamics. Previous work has shown that task allocation using a market-based mechanism can provide scalable and efficient management of static networks; in this paper we extend this work to determine the impact of dynamic topologies. We develop a Keplerian mobility model to describe the topology of the communication network over time. This movement model is then used in simulation to show that the task allocation mechanism does not show a significant decrease in effectiveness from the static case, reflecting the suitability distributed market-based control to the highly dynamic environment
Task allocation in networks of satellites with Keplerian dynamics
No full textThe management of distributed satellite systems requires the coordination of a large number of heterogeneous spacecraft. Task allocation in such a system is complicated by limited communication and individual satellite dynamics. Previous work has shown that task allocation using a market-based mechanism can provide scalable and efficient management of static networks; in this paper we extend this work to determine the impact of dynamic topologies. We develop a Keplerian mobility model to describe the topology of the communication network over time. This movement model is then used in simulation to show that the task allocation mechanism does not show a significant decrease in effectiveness from the static case, reflecting the suitability of distributed market-based control to the highly dynamic environment
Reviewing the EU Emissions Trading Scheme: Priorities for Short-Term Implementation of the Second Round of Allocation (Part I). CEPS Task Force Reports No. 56 (57?), 1 December 2005
No full textThis report presents the findings of a multi-stakeholder CEPS Task Force, co-chaired by David Hone, Shell and Lasse Nord, Norsk Hydro. After taking stock of the EU ETS, the report examines the need and potential for short-term adaptation of the second round of allocation and makes concrete and operational recommendations to EU member states and the European Commission
Decentralised Dynamic Task Allocation Using Overlapping Potential Games
No full textThis paper reports on a novel decentralised technique for planning agent schedules in dynamic task allocation problems. Specifically, we use a stochastic game formulation of these problems in which tasks have varying hard deadlines and processing requirements. We then introduce a new technique for approximating this game using a series of static potential games, before detailing a decentralised method for solving the approximating games that uses the distributed stochastic algorithm. Finally, we discuss an implementation of our approach to a task allocation problem in the RoboCup Rescue disaster management simulator. The results show that our technique performs comparably to a centralised task scheduler (within 6% on average), and also, unlike its centralised counterpart, it is robust to restrictions on the agents’ communication and observation ranges
Design and Modelling of Decentralised Task Allocation Mechanisms in Groups of Mobile Agents
No full textDivision of labour is a fundamental field of research within the context of multi-agent (particularly swarm based systems) and multi-robot systems. Eusocial insects, for instance ants and bees, are known to display remarkable capabilities of allocating tasks to nest mates when the colony gets perturbed by any internal and/or external factors. Proper understanding of the underlying mechanisms of division of labour among these social insects would enable more effective designing and developing of artificial swarm based systems which in turn can be used in tackling various real world problems. At the same time, a properly built model can be used to serve as a platform for the biologists to test their research hypotheses. These key benefits have been the prime motivations of this thesis. The thesis is based on the behaviour of ant colonies and especially on how they allocate tasks in different situations. The objectives of the thesis are twofold: (1) to develop an artificial simulated system that is ant-like and (2) to explore, identify, develop and analyse task allocation strategies within the realms of colony performance.
The first objective of the thesis is approached by investigating the behaviour of ant colonies from the existing literature and modelling their behaviours using an agent based modelling approach. To determine whether the model has met the first objective, three questions are posed: (A) Is the emergent system scalable? (B) Is the emergent system flexible? and (C) Is the system robust? For a system to be ant-like, the system has to not only give the appearance of ant-like behaviour but also has to meet these three criteria. As a part of the second objective of the thesis, three task allocation strategies based on ant colony behaviour are proposed. Furthermore, the strategies are critically analysed to investigate the benefits of each of the strategies and also to discover under what circumstances which strategies would perform better. The research reported in this thesis is intended to provide a better understanding of the design issues of task allocation strategies thus enabling researchers to use this as a guide to design effective task allocation strategies within the concerned multi-agent systems
Distributed and Centralized Task Allocation: When and Where to Use Them
No full textSelf-organisation is frequently advocated as the solution for managing large, dynamic systems. Distributed algorithms are implicitly designed for infinitely large problems, while small systems are regarded as being controllable using traditional, centralised approaches. Many real-world systems, however, do not fit conveniently into these "small" or "large" categories, resulting in a range of cases where the optimal solution is ambiguous. This difficulty is exacerbated by enthusiasts of either approach constructing problems that suit their preferred control architecture. We address this ambiguity by building an abstract model of task allocation in a community of specialised agents. We are inspired by the problem of work distribution in distributed satellite systems, but the model is also relevant to the resource allocation problems in distributed robotics, autonomic computing and wireless sensor networks. We compare the behaviour of a self-organising, market-based task allocation strategy to a classical approach that uses a central controller with global knowledge. The objective is not to prove one mechanism inherently superior to the other; instead we are interested in the regions of problem space where each of them dominates. Simulation is used to explore the trade-off between energy consumption and robustness in a system of intermediate size, with fixed communication costs and varying rates of component failure. We identify boundaries between regions in the parameter space where one or the other architecture will be favoured. This allows us to derive guidelines for system designers, thus contributing to the development of a disciplined approach to controlling distributed systems using self-organising mechanisms
Risk allocation strategies for distributed chance-constrained task allocation
No full textThis paper addresses the issue of allocating risk amongst agents in distributed chance-constrained planning algorithms. Building on previous research that extended chance-constrained planning to stochastic multi-agent multi-task missions, this paper presents a framework for risk allocation and proposes several strategies for distributing risk in homogeneous and heterogeneous teams. In particular, the contributions of this work include: proposing risk allocation strategies that exploit domain knowledge of agent score distributions to improve team performance, providing insights about what stochastic parameters affect the allocations and the overall mission score/performance, and providing results showing improved performance over previously published heuristic techniques in environments with given allowable risk thresholds.United States. Air Force Office of Scientific Research (FA9550-08-1-0086)United States. Multidisciplinary University Research Initiative (FA9550-08-1-0356
Decentralised Dynamic Task Allocation: A Practical Game–Theoretic Approach
No full textThis paper reports on a novel decentralised technique for planning agent schedules in dynamic task allocation problems. Specifically, we use a Markov game formulation of these problems for tasks with varying hard deadlines and processing requirements. We then introduce a new technique for approximating this game using a series of static potential games, before detailing a decentralised solution method for the approximating games that uses the Distributed Stochastic Algorithm. Finally, we discuss an implementation of our approach to a task allocation problem in the RoboCup Rescue disaster management simulator. Our results show that our technique performs comparably to a centralised task scheduler (within 6% on average), and also, unlike its centralised counterpart, it is robust to restrictions on the agents' communication and observation range
Centralized versus market-based approaches to mobile task allocation problem: State-of-the-art
No full textCentralized approach has been adopted for finding solutions to resource allocation problems (RAPs) in many real-life applications. On the other hand, market-based approach has been proposed as an alternative to solve the problem due to recent advancement in ICT technologies. In spite of the existence of some efforts to review the pros and cons of each approach in RAPs, the studies cannot be directly applied to specific problem domains like mobile task allocation problem which is characterised with high level of uncertainty on the availability of resources (workers). This paper aims to review existing studies on task allocation problems(TAPs) focusing on those two approaches and their comparison and identify major issues that need to be resolved for comparing the two approaches in mobile task allocation problems. Mobile Task Allocation Problem (MTAP) is defined and its problematic structures are explained in relation with task allocation to mobile workers. Solutions produced by each approach to some applications and variations of MTAP are also discussed and compared. Finally, some future research directions are identified in order to compare both approaches in function of uncertainty emerging from the mobile nature of the MTAP
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