A Multiagent Approach Towards Solving Complex Problems of Sociotechnical Systems

Complex resource allocation problems arise due to complex human societies and scarce resources to be distributed. Scarce resources could be food, water, and energy. Meanwhile, the size of the problem, the intersection of different areas, and possible global consequences all add to the complexity of the problems, which makes it difficult for humans to solve the problems by themselves. For all these reasons, humans need technical help to tackle complex problems. Since humans participating in the problems usually own part of the information about the problems, and no one may see the whole picture of the problems, it is natural to use distributed systems to simulate and analyze the problems. In a distributed system, humans represented by agents knowing only partial information interact with each other in order to achieve a common goal while maximizing their own interests. The resultant distributed system is called a multiagent system, because multiple agents are involved in the systems. In this dissertation, we study three cases of multiagent systems that help with distributing a certain kind of resource. First, we present an approach to assist individuals shop for groceries. The aim is to help a customer to find the most economical way of shopping. We show that a customer could save 22% or more most of the time with simulated price data and 6.7% with real price data. Robustness is also considered with deceptive stores and wrongly reported prices. Second, we simulate a healthcare system in which agents are used to assist a patient to find a physician. We investigate four different strategies for assisting a person in choosing a physician and three physician-waiting policies in three common social network models. The results show that the resultant sociotechnical system can decrease the number of annual sick days per person by 0.4-1.8 days compared with choosing a physician randomly. Third we investigate the influence of humans\u27 personalities on resource allocation in mixed human-agent societies. It is shown that humans treat other humans and agents differently and humans with different temperaments behave differently, but not with significantly difference, which means fair is more important than personality types while making decisions. The three cases investigate different aspects of a sociotechnical system. The grocery-shopping case involves agents that interact with each other indirectly through a central aggregator of local results. The physician choosing case involves agents that interact with each other directly in a social network that is a subset of the complete network of agents. The resource-allocation case investigates the relationships between the agents and the humans in a sociotechnical system

Systems modelling of the South African offshore demersal hake trawl fishery : an economic perspective

The offshore demersal hake trawl is the largest sector of the South African hake fishery, which targets shallow-water (Merluccius capensis) and deep-water (M. paradoxus) Cape hakes. Economically, it is the most important fishery in South Africa, generating ZAR ~5 billion in revenue, mainly from exports, and it supports an estimated 30 000 jobs. Whereas there are a number of single-species and ecosystem models that assess hake stock dynamics and examine the food web dynamics of the southern Benguela ecosystem, the human social hake fishery system is less understood. In order to address this need, this study's aims are to i) analyse the structure and dynamics of the economics of the South African offshore demersal hake trawl fishery from empirical data and stakeholder interviews, and ii) produce a prototype economic simulation model of this fishery to better understand the dynamics of the industry and the relative importance of its internal and external drivers, e.g. industrial organization, environmental uncertainty, exchange rate and fuel price. The empirical analyses confirm that the offshore hake trawl fishery is an economically mature and highly vertically integrated industry. That is, most companies control much of the value-chain, catching, processing, marketing and distributing their fish products, with access to economies of scope and scale. Nine company clusters, formed through consolidation of fishing rights and a variety of catch-share agreements, have been identified. Based on their size and operations they have been categorized as small, medium, large and super-cluster types. Fishing vessel numbers have declined since 1978 to streamline operations, with current effort optimising restrictions based on vessel engine power and the ability to catch the full quota. During the observation period (2005-2012), high-value export markets have bought 60-70% of the South African hake total allowable catch (TAC), comprising nine major markets and a number of smaller ones. The lower-value domestic market takes ca. 30% plus imports equivalent to another ca. 15% of TAC. Hake export volumes have shifted from fresh to frozen and increasingly to value-added products, especially after the 2008 banking crisis. This corresponds to an industry-confirmed price-convergence between fresh and frozen hake products. This product displacement trend is largely due to changes in the largest export market, Spain, and is mirrored by an increased reliance on freezer trawling in the industry