The effect of social influence and curfews on civil violence

We investigate the policies of (1) restricting social influence and (2) imposing curfews upon interacting citizens in a community. We compare and contrast their effects on the social order and the emerging levels of civil violence. Influence models have been used in the past in the context of decision making in a variety of application domains. The policy of curfews has been utilised with the aim of curbing social violence but little research has been done on its effectiveness. We develop a multi-agent-based model that is used to simulate a community of citizens and the police force that guards it. We find that restricting social influence does indeed pacify rebellious societies, but has the opposite effect on peaceful ones. On the other hand, our simple model indicates that restricting mobility through curfews has a pacifying effect across all types of society.

Evolution of competing strategies in a threshold model for task allocation

A nature inspired decentralised multi-agent algorithm is proposed to solve a problem of distributed task allocation in which cities produce and store batches of different mail types. Agents must collect and process the mail batches, without global knowledge of their environment or communication between agents. The problem is constrained so that agents are penalised for switching mail types. When an agent process a mail batch of different type to the previous one, it must undergo a change-over, with repeated change-overs rendering the agent inactive. The efficiency (average amount of mail retrieved), and the flexibility (ability of the agents to react to changes in the environment) are investigated both in static and dynamic environments and with respect to sudden changes. New rules for mail selection and specialisation are proposed and are shown to exhibit improved efficiency and flexibility compared to existing ones. We employ a evolutionary algorithm which allows the various rules to evolve and compete. Apart from obtaining optimised parameters for the various rules for any environment, we also observe extinction and speciation.

The influence of memory in a threshold model for distributed task assignment

A nature inspired decentralised multi-agent algorithm is proposed to solve a problem of distributed task selection in which cities produce and store batches of different mail types. Agents must collect and process the mail batches, without a priori knowledge of the available mail at the cities or inter-agent communication. In order to process a different mail type than the previous one, agents must undergo a change-over during which it remains inactive. We propose a threshold based algorithm in order to maximise the overall efficiency (the average amount of mail collected). We show that memory, i.e. the possibility for agents to develop preferences for certain cities, not only leads to emergent cooperation between agents, but also to a significant increase in efficiency (above the theoretical upper limit for any memoryless algorithm), and we systematically investigate the influence of the various model parameters. Finally, we demonstrate the flexibility of the algorithm to changes in circumstances, and its excellent scalability.

Local economic development initiatives and the transition from training and enterprise councils to new institutional structures in England

Current British government economic development policy emphasises regional and sub-regional scale, multi-agent initiatives that form part of national frameworks to encourage a 'bottom up' approach to economic development. An emphasis on local multi-agent initiatives was also the mission of Training and Enterprise Councils (TECs). Using new survey evidence this article tracks the progress of a number of initiatives established under the TECs, using the TEC Discretionary Fund as an example. It assesses the ability of successor bodies to be more effective in promoting local economic development. Survey evidence is used to confirm that many projects previously set up by the TECs continue to operate successfully under new partnership arrangements. However as new structures have developed, and policy has become more centralized, it is less likely that similar local initiatives will be developed in future. There is evidence to suggest that with the end of the TECs a gap has emerged in the institutional infrastructure for local economic development, particularly with regard to workforce development. Much will depend in future on how the Regional Development Agencies deploy their growing power and resources.

An efficient knowledge transfer solution to a novel SMDP formalization of a broker's decision problem

This paper introduces a new technique for optimizing the trading strategy of brokers that autonomously trade in re- tail and wholesale markets. Simultaneous optimization of re- tail and wholesale strategies has been considered by existing studies as intractable. Therefore, each of these strategies is optimized separately and their interdependence is generally ignored, with resulting broker agents not aiming for a glob- ally optimal retail and wholesale strategy. In this paper, we propose a novel formalization, based on a semi-Markov deci- sion process (SMDP), which globally and simultaneously op- timizes retail and wholesale strategies. The SMDP is solved using hierarchical reinforcement learning (HRL) in multi- agent environments. To address the curse of dimensionality, which arises when applying SMDP and HRL to complex de- cision problems, we propose an ecient knowledge transfer approach. This enables the reuse of learned trading skills in order to speed up the learning in new markets, at the same time as making the broker transportable across market envi- ronments. The proposed SMDP-broker has been thoroughly evaluated in two well-established multi-agent simulation en- vironments within the Trading Agent Competition (TAC) community. Analysis of controlled experiments shows that this broker can outperform the top TAC-brokers. More- over, our broker is able to perform well in a wide range of environments by re-using knowledge acquired in previously experienced settings.

Optimising market share and profit margin:SMDP-based tariff pricing under the smart grid paradigm

Smart grid technologies have given rise to a liberalised and decentralised electricity market, enabling energy providers and retailers to have a better understanding of the demand side and its response to pricing signals. This paper puts forward a reinforcement-learning-powered tool aiding an electricity retailer to define the tariff prices it offers, in a bid to optimise its retail strategy. In a competitive market, an energy retailer aims to simultaneously increase the number of contracted customers and its profit margin. We have abstracted the problem of deciding on a tariff price as faced by a retailer, as a semi-Markov decision problem (SMDP). A hierarchical reinforcement learning approach, MaxQ value function decomposition, is applied to solve the SMDP through interactions with the market. To evaluate our trading strategy, we developed a retailer agent (termed AstonTAC) that uses the proposed SMDP framework to act in an open multi-agent simulation environment, the Power Trading Agent Competition (Power TAC). An evaluation and analysis of the 2013 Power TAC finals show that AstonTAC successfully selects sell prices that attract as many customers as necessary to maximise the profit margin. Moreover, during the competition, AstonTAC was the only retailer agent performing well across all retail market settings.

Analysis and design of power management scheme for an on-board solar energy storage system

This paper investigates the power management issues in a mobile solar energy storage system. A multi-converter based energy storage system is proposed, in which solar power is the primary source while the grid or the diesel generator is selected as the secondary source. The existence of the secondary source facilitates the battery state of charge detection by providing a constant battery charging current. Converter modeling, multi-converter control system design, digital implementation and experimental verification are introduced and discussed in details. The prototype experiment indicates that the converter system can provide a constant charging current during solar converter maximum power tracking operation, especially during large solar power output variation, which proves the feasibility of the proposed design. © 2014 IEEE.

Maximising the efficiency of logistics operations with radio frequency identification technology

Radio frequency identification (RFID) technology has gained increasing popularity in businesses to improve operational efficiency and maximise costs saving. However, there is a gap in the literature exploring the enhanced use of RFID to substantially add values to the supply chain operations, especially beyond what the RFID vendors could offer. This paper presents a multi-agent system, incorporating RFID technology, aimed at fulfilling the gap. The system is developed to model supply chain activities (in particular, logistics operations) and is comprised of autonomous and intelligent agents representing the key entities in the supply chain. With the advanced characteristics of RFID incorporated, the agent system examines ways logistics operations (i.e. distribution network) particular) can be efficiently reconfigured and optimised in response to dynamic changes in the market, production and at any stage in the supply chain. © 2012 IEEE.

Design methodology for the servo control of high speed multi-axis machinery (BL): decoupling and synchronisation of a generic machine by blockwise decentralised MIMO control

Traditional machinery for manufacturing processes are characterised by actuators powered and co-ordinated by mechanical linkages driven from a central drive. Increasingly, these linkages are replaced by independent electrical drives, each performs a different task and follows a different motion profile, co-ordinated by computers. A design methodology for the servo control of high speed multi-axis machinery is proposed, based on the concept of a highly adaptable generic machine model. In addition to the dynamics of the drives and the loads, the model includes the inherent interactions between the motion axes and thus provides a Multi-Input Multi-Output (MIMO) description. In general, inherent interactions such as structural couplings between groups of motion axes are undesirable and needed to be compensated. On the other hand, imposed interactions such as the synchronisation of different groups of axes are often required. It is recognised that a suitable MIMO controller can simultaneously achieve these objectives and reconciles their potential conflicts. Both analytical and numerical methods for the design of MIMO controllers are investigated. At present, it is not possible to implement high order MIMO controllers for practical reasons. Based on simulations of the generic machine model under full MIMO control, however, it is possible to determine a suitable topology for a blockwise decentralised control scheme. The Block Relative Gain array (BRG) is used to compare the relative strength of closed loop interactions between sub-systems. A number of approaches to the design of the smaller decentralised MIMO controllers for these sub-systems has been investigated. For the purpose of illustration, a benchmark problem based on a 3 axes test rig has been carried through the design cycle to demonstrate the working of the design methodology.

Discontinuous control of multi-variable processes

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A coordinated control scheme for power demand changes in a PMSG based multi-terminal DC wind farm

Although maximum power point tracking (MPPT) is crucial in the design of a wind power generation system, the necessary control strategies should also be considered for conditions that require a power reduction, called de-loading in this paper. A coordinated control scheme for a proposed current source converter (CSC) based DC wind energy conversion system is presented in this paper. This scheme combines coordinated control of the pitch angle, a DC load dumping chopper and the DC/DC converter, to quickly achieve wind farm de-loading. MATLAB/Simulink simulations and experiments are used to validate the purpose and effectiveness of the control scheme, both at the same power level. © 2013 IEEE.