General rules for environmental management to prioritise social ecological systems research based on a value of information approach

This is the final version. Available on open access from Wiley via the DOI in this record1. Globally, billions of dollars are invested each year to help understand the dynamics of social ecological systems (SES) in bettering both social and environmental outcomes. However, there is no scientific consensus on which aspect of an SES is most important and urgent to understand; particularly given the realities of limited time and money. 2. Here we use a simulation‐based “value of information” approach to examine where research will deliver the most important information for environmental management in four SESs representing a range of real‐life environmental issues. 3. We find that neither social nor ecological information is consistently the most important: instead, researchers should focus on understanding the primary effects of their management actions. 4. Thus, when managers are undertaking social actions the highest research priority should be understanding the dynamics of social groups. Alternatively, when manipulating ecological systems it will be most important to quantify ecological population dynamics. 5. Synthesis and applications. Our results provide a standard assessment to determine the uncertain social ecological systems (SES) component with the highest expected impact for management outcomes. First, managers should determine the structure of their SES by identifying social and ecological nodes. Second, managers should identify the qualitative nature of the network, by determining which nodes are linked, but not the strength of those interactions. Finally, managers should identify the actions available to them to intervene in the SES. From these steps, managers will be able to identify the SES components that are closest to the management action(s), and it is these nodes and interactions that should receivepriority research attention to achieve effective environmental decision making.Centre of Excellence for Environmental Decisions, Australian Research Counc

Bilateral negotiation in a multi-agent supply chain system

A supply chain is a set of organizations directly linked by flows of services from suppliers to customers. Supply chain activities range from the ordering and receipt of raw materials to the production and distribution of finished goods. Supply chain management is the integration of key activities across a supply chain for the purposes of building competitive infrastructures, synchronizing supply with demand, and leveraging worldwide logistics. This paper addresses the challenges created by supply chain management towards improving long-term performance of companies. It presents a multi-agent supply chain system composed of multiple software agents, each responsible for one or more supply chain activities, and each interacting with other agents in the execution of their responsibilities. Additionally, this paper presents the key features of a negotiation model for software agents. The model handles bilateral multi-issue negotiation and incorporates an alternating offers protocol, a set of logrolling strategies, and a set of negotiation tactics

Flexible provisioning of Web service workflows

Web services promise to revolutionise the way computational resources and business processes are offered and invoked in open, distributed systems, such as the Internet. These services are described using machine-readable meta-data, which enables consumer applications to automatically discover and provision suitable services for their workflows at run-time. However, current approaches have typically assumed service descriptions are accurate and deterministic, and so have neglected to account for the fact that services in these open systems are inherently unreliable and uncertain. Specifically, network failures, software bugs and competition for services may regularly lead to execution delays or even service failures. To address this problem, the process of provisioning services needs to be performed in a more flexible manner than has so far been considered, in order to proactively deal with failures and to recover workflows that have partially failed. To this end, we devise and present a heuristic strategy that varies the provisioning of services according to their predicted performance. Using simulation, we then benchmark our algorithm and show that it leads to a 700% improvement in average utility, while successfully completing up to eight times as many workflows as approaches that do not consider service failures

Quantum decision making by social agents

The influence of additional information on the decision making of agents, who are interacting members of a society, is analyzed within the mathematical framework based on the use of quantum probabilities. The introduction of social interactions, which influence the decisions of individual agents, leads to a generalization of the quantum decision theory developed earlier by the authors for separate individuals. The generalized approach is free of the standard paradoxes of classical decision theory. This approach also explains the error-attenuation effects observed for the paradoxes occurring when decision makers, who are members of a society, consult with each other, increasing in this way the available mutual information. A precise correspondence between quantum decision theory and classical utility theory is formulated via the introduction of an intermediate probabilistic version of utility theory of a novel form, which obeys the requirement that zero-utility prospects should have zero probability weights.Comment: This paper has been withdrawn by the authors because a much extended and improved version has been submitted as arXiv:1510.02686 under the new title "Role of information in decision making of social agents

Bounded rationality and the Brexit negotiations:Why Britain failed to understand the EU

Research on the Brexit negotiations has linked the problems faced by Britain to flawed assumptions in the UK’s perception of EU interests. These include the idea that the EU would be open to compromise on key principles, that it would offer the UK a bespoke relationship, that national capitals would respond favourably to bilateral initiatives, and that EU unity would not hold. Yet the origins of these assumptions have been subject to little systematic scrutiny. How did such wrong-headed assumptions about the EU’s interests emerge? Drawing on insights from bounded rationality we identify three aspects of the decision-making environment linked with biased thinking: (1) ill-fitting routines and lessons, (2) a lack of decision-making openness, and (3) a lack of EU expertize and contact. We demonstrate our argument using data obtained from interviews in Brussels and London in 2017–18 and accounts of those involved in the decisions

Brexit negotiations: from negotiation space to agreement zones

Brexit is decidedly a “big question”. We agree with International Business scholars who say that such questions need to be addressed using an inter-disciplinary approach. We use bargaining theory models of rational behavior and the negotiation literature to explain various Brexit options and predict their consequences. Considering the lack of relevant experiential knowledge, and the multidimensional high-stakes negotiations underway, it is little wonder that anxiety is growing across all 28 European Union member states. Our analysis supports a coherent approach from rational bargaining model to real-life international negotiation. We position outcome scenarios in different agreement zones and explore their ramifications