Learning in evolutionary environments

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Learning in Evolutionary Environments

The purpose of this work is to present a sort of short selective guide to an enormous and diverse literature on learning processes in economics. We argue that learning is an ubiquitous characteristic of most economic and social systems but it acquires even greater importance in explicitly evolutionary environments where: a) heterogeneous agents systematically display various forms of "bounded rationality"; b) there is a persistent appearance of novelties, both as exogenous shocks and as the result of technological, behavioural and organisational innovations by the agents themselves; c) markets (and other interaction arrangements) perform as selection mechanisms; d) aggregate regularities are primarily emergent properties stemming from out-of-equilibrium interactions. We present, by means of examples, the most important classes of learning models, trying to show their links and differences, and setting them against a sort of ideal framework of "what one would like to understand about learning...". We put a signifiphasis on learning models in their bare-bone formal structure, but we also refer to the (generally richer) non-formal theorising about the same objects. This allows us to provide an easier mapping of a wide and largely unexplored research agenda.Learning, Evolutionary Environments, Economic Theory, Rationality

Mental models or probabilistic reasoning or both: Reviewing the evidence for and implications of dual-strategy models of deductive reasoning

The present paper presents an overview of contemporary reasoning research to examine the evidence for and implications of the Dual Strategy Model of Reasoning. The Dual Strategy Model of Reasoning proposes that there are two types of reasoning strategy applied in deductive reasoning – counterexample and statistical. The paper considers Mental Models Theory and The Probability Heuristics Model as candidate specifications for these respective strategies and hypotheses are proposed on this basis. The Dual Strategy Model is further considered in the context of Dual Process theory, the Dual Source Model and Meta-reasoning and implications of the synergy between these proposals are considered. We finally consider the Dual Strategy Model in the context of individual differences, and normative considerations before proposing novel hypotheses and further avenues of research which we argue require exploration in this context.N/

Surveying human habit modeling and mining techniques in smart spaces

A smart space is an environment, mainly equipped with Internet-of-Things (IoT) technologies, able to provide services to humans, helping them to perform daily tasks by monitoring the space and autonomously executing actions, giving suggestions and sending alarms. Approaches suggested in the literature may differ in terms of required facilities, possible applications, amount of human intervention required, ability to support multiple users at the same time adapting to changing needs. In this paper, we propose a Systematic Literature Review (SLR) that classifies most influential approaches in the area of smart spaces according to a set of dimensions identified by answering a set of research questions. These dimensions allow to choose a specific method or approach according to available sensors, amount of labeled data, need for visual analysis, requirements in terms of enactment and decision-making on the environment. Additionally, the paper identifies a set of challenges to be addressed by future research in the field

An overview of decision table literature 1982-1995.

This report gives an overview of the literature on decision tables over the past 15 years. As much as possible, for each reference, an author supplied abstract, a number of keywords and a classification are provided. In some cases own comments are added. The purpose of these comments is to show where, how and why decision tables are used. The literature is classified according to application area, theoretical versus practical character, year of publication, country or origin (not necessarily country of publication) and the language of the document. After a description of the scope of the interview, classification results and the classification by topic are presented. The main body of the paper is the ordered list of publications with abstract, classification and comments.

Policy Evaluation in Uncertain Economic Environments

This paper develops a decision-theoretic approach to policy analysis. We argue that policy evaluation should be conducted on the basis of two factors: the policymaker's preferences, and the conditional distribution of the outcomes of interest given a policy and available information. From this perspective, the common practice of conditioning on a particular model is often inappropriate, since model uncertainty is an important element of policy evaluation. We advocate the use of model averaging to account for model uncertainty and show how it may be applied to policy evaluation exercises. We illustrate our approach with applications to monetary policy and to growth policy.

Mapping the intuitive investigation: Seeking, evaluating and explaining the evidence

The human mind has developed numerous cognitive tools to allow us to navigate the uncertainty of the world and make sense of situations and events. In this thesis I present a descriptive account of some of these tools by probing people’s ability to: evaluate, seek, and explain evidence and information. This was achieved by appraising people’s behaviour in controlled experiments – predominantly representing legal-investigative scenarios – utilising normative causal models (e.g., causal Bayesian networks), and uncovering the alternative strategies that people employed when reasoning under uncertainty. In Chapter 4, I investigate people’s ability to engage in a pattern of reasoning termed ‘explaining away’ and propose, and find empirical support towards, intuitive theories that address why the observed inference errors were made. In Chapter 5, I outline how people search for, and evaluate, evidence in a sequential investigative information-seeking paradigm – finding that people do not seek information simply to maximize a given utility function but rather are driven by additional strategies which are sensitive to factors such as demands of the task and a novel form of risk aversion. I extend these findings to forensic professionals, and utilise a naturalistic study employing mobile eye-trackers during a mock crime scene investigation to elucidate the key role that ‘asking the right questions’ plays when engaging in sense-making practices ‘in the wild’. In Chapter 6, I explore people’s preferences for certain types of information relating to opportunity and motive at various stages of the legal-investigative process. Here, I demonstrate that people prefer ‘motive’ accounts of crimes (analogous to a teleology preference) at different stages of the investigative process. In an additional two studies I demonstrate that these preferences are context-sensitive: namely, that ‘motive’ information tends to be moreincriminating and less exculpatory. In a final set of experiments, outlined in Chapter 7, I investigate how drawing causal models of competing explanations of the evidence affects how these same explanations are evaluated – arguing that graphically representing the evidence bolsters people’s understanding of the probabilistic and logical significance of the causal structures drawn. In sum, this thesis provides a rich descriptive account of how people engage in various aspects of sense-making and decision-making under uncertainty. The work presented in this thesis ultimately aims to increase the ecological and descriptive validity of normative causal frameworks utilised in the cognitive sciences – whilst informing ways to formalise decision-making practices in real-world specialised domains