Structuring the decision process : an evaluation of methods in the structuring the decision process

This chapter examines the effectiveness of methods that are designed to provide structure and support to decision making. Those that are primarily aimed at individual decision makers are examined first and then attention is turned to groups. In each case weaknesses of unaided decision making are identified and how successful the application of formal methods is likely to be in mitigating these weaknesses is assessed

Which heuristics can aid financial-decision-making?

© 2015 Elsevier Inc. We evaluate the contribution of Nobel Prize-winner Daniel Kahneman, often in association with his late co-author Amos Tversky, to the development of our understanding of financial decision-making and the evolution of behavioural finance as a school of thought within Finance. Whilst a general evaluation of the work of Kahneman would be a massive task, we constrain ourselves to a more narrow discussion of his vision of financial-decision making compared to a possible alternative advanced by Gerd Gigerenzer along with numerous co-authors. Both Kahneman and Gigerenzer agree on the centrality of heuristics in decision making. However, for Kahneman heuristics often appear as a fall back when the standard von-Neumann-Morgenstern axioms of rational decision-making do not describe investors' choices. In contrast, for Gigerenzer heuristics are simply a more effective way of evaluating choices in the rich and changing decision making environment investors must face. Gigerenzer challenges Kahneman to move beyond substantiating the presence of heuristics towards a more tangible, testable, description of their use and disposal within the ever changing decision-making environment financial agents inhabit. Here we see the emphasis placed by Gigerenzer on how context and cognition interact to form new schemata for fast and frugal reasoning as offering a productive vein of new research. We illustrate how the interaction between cognition and context already characterises much empirical research and it appears the fast and frugal reasoning perspective of Gigerenzer can provide a framework to enhance our understanding of how financial decisions are made

Human Dimensions of the Ecosystem Approach to Fisheries: An Overview of Context, Concepts, Tools and Methods

This document aims to provide a better understanding of the role of the economic, institutional and sociocultural components within the ecosystem approach to fisheries (EAF) process and to examine some potential methods and approaches that may facilitate the adoption of EAF management. It explores both the human context for the ecosystem approach to fisheries and the human dimensions involved in implementing the EAF. For the former, the report provides background material essential to understand prior to embarking on EAF initiatives, including an understanding of key concepts and issues, of the valuation of aquatic ecosystems socially, culturally and economically, and of the many policy, legal, institutional, social and economic considerations relevant to the EAF. With respect to facilitating EAF implementation, the report deals with a series of specific aspects: (1) determining the boundaries, scale and scope of the EAF; (2) assessing the various benefits and costs involved, seen from social, economic, ecological and management perspectives; (3) utilizing appropriate decision-making tools in EAF; (4) creating and/or adopting internal incentives and institutional arrangements to promote, facilitate and fund the adoption of EAF management; and (5) finding suitable external (non-fisheries) approaches for financing EAF implementation

On the Evolution of Knowledge Graphs: A Survey and Perspective

Knowledge graphs (KGs) are structured representations of diversified knowledge. They are widely used in various intelligent applications. In this article, we provide a comprehensive survey on the evolution of various types of knowledge graphs (i.e., static KGs, dynamic KGs, temporal KGs, and event KGs) and techniques for knowledge extraction and reasoning. Furthermore, we introduce the practical applications of different types of KGs, including a case study in financial analysis. Finally, we propose our perspective on the future directions of knowledge engineering, including the potential of combining the power of knowledge graphs and large language models (LLMs), and the evolution of knowledge extraction, reasoning, and representation

Living the Transition. A Bottom-up Perspective on Rwanda’s Political Transition

Political transitions are dominantly analyzed top-down and focus on a narrow range of political processes and institutions. Critical rethinkings of the ‘transition paradigm’ entail that structural factors, such as historical legacies and ethnic make-up, determine the trajectory of political transitions. In this paper we intend to complement top-down approaches by offering a bottom-up perspective revealing what it means to live through a transition in the ordinary perception. We use the Rwandan transition as case-study. An analysis of over 400 life histories of ordinary Rwandan peasants and their subjective ranking exercises over time on a ‘ladder of life’ portrays the trajectory of the Rwandan transition as perceived from below. The ethnicity of the respondents functions as pivot to shed light on the structural factor underlying the Rwandan transition: the Hutu-Tutsi bi-polarity.

In the shadow of the ICC: Colombia and international criminal justice

The report of the expert conference examining the nature and dynamics of the role of the International Criminal Court in the ongoing investigation and prosecution of atrocious crimes committed in Colombia. Convened by the Human Rights Consortium, the Institute of Commonwealth Studies and the Institute for the Study of the Americas at the School of Advanced Study, University of London University of London, 26–27 May 2011

Social Interaction Effects on Reward and Cognitive Abilities in Monkeys

When given a choice between receiving $100 in 30 days and$110 in 31 days, most people wait for the larger, more delayed reward. However, when the choice is between $100 today and$110 tomorrow, many people shift their preferences to the smaller, immediate reward despite the same difference of $10 and one day. Reward properties—such as time to receipt—play a crucial role in our processing of rewards. However, reward processing does not only occur for individual decisions but also for social interactions; we must decide to either cooperate or compete with others for rewards. Humans stand out in the animal kingdom as exceptional cooperators, both in terms of the form that cooperation assumes as well as the nature of rewards attained. Regarding form, we are unique in the stability of our reciprocal interactions and in the scale of our cooperative coalitions, entailing multiple nation states in times of war. In terms of rewards, we are of course motivated, like all other animals, by the central survival payoffs such as food and water but also by abstract entities such as money, the promise of future support, and positions of power such as a king, president, or head of an academic department. To maintain these complicated interactions and evaluate the nature of reward, we must possess a number of prerequisite cognitive abilities. Here, we view this problem through the lens of evolutionary biology, asking which aspects of our cognitive machinery, and the social interactions it supports, are uniquely human and which are shared with other primates. Though we focus on lemurs, monkeys, and apes, we acknowledge that many of the processes we document are unlikely to be restricted to the primates, and in many cases, there is already comparable evidence from other mammals and birds. We begin by reviewing a suite of cognitive mechanisms that are involved in both human and nonhuman primate reward processing. Our review is particularly focused on the subset of situations with quantifiable rewards. We then describe the kinds of social interactions that are part and parcel of primate life, especially the highly social monkeys and apes. Lastly, we merge these two sections and consider how constraints on primate cognition may limit the complexity of primate social interactions