Linking objective and subjective modeling in engineering design through arc-elastic dominance

Engineering design in mechanics is a complex activity taking into account both objective modeling processes derived from physical analysis and designers’ subjective reasoning. This paper introduces arc-elastic dominance as a suitable concept for ranking design solutions according to a combination of objective and subjective models. Objective models lead to the aggregation of information derived from physics, economics or eco-environmental analysis into a performance indicator. Subjective models result in a confidence indicator for the solutions’ feasibility. Arc-elastic dominant design solutions achieve an optimal compromise between gain in performance and degradation in confidence. Due to the definition of arc-elasticity, this compromise value is expressive and easy for designers to interpret despite the difference in the nature of the objective and subjective models. From the investigation of arc-elasticity mathematical properties, a filtering algorithm of Pareto-efficient solutions is proposed and illustrated through a design knowledge modeling framework. This framework notably takes into account Harrington’s desirability functions and Derringer’s aggregation method. It is carried out through the re-design of a geothermal air conditioning system

The naturalistic turn in economics: implications for the theory of finance

Economics is increasingly adopting the methodological standards and procedures of the natural sciences. The paper analyzes this 'naturalistic turn' from the philosophical perspective on naturalism, and I discuss the implications for the field of finance. The theory of finance is an interesting case in point for the methodological issues, as it manifests a paradigmatic tension between the pure theory of finance and Behavioral Finance. I distinguish between three kinds of naturalism: mark I, the reduction of behavior on psychoneural phenomena, mark II, the transfer of patterns of causal explanations from the natural sciences to the social sciences, mark III, the enrichment of the ontology from observer-independent to observer-relative facts. Building an integrated naturalistic paradigm from these three ingredients, I show that naturalism in economics will only be completed by a simultaneous linguistic turn, with language being analyzed from the naturalistic viewpoint. I relate this proposition with recent results of research into finance, especially connecting Behavioral Finance with the sociology of finance. --Naturalism,causation in economics,neuroeconomics,behavioral finance,social ontology,sociology of finance

Computational Rationality: Linking Mechanism and Behavior Through Bounded Utility Maximization

We propose a framework for including information‐processing bounds in rational analyses. It is an application of bounded optimality (Russell & Subramanian, 1995) to the challenges of developing theories of mechanism and behavior. The framework is based on the idea that behaviors are generated by cognitive mechanisms that are adapted to the structure of not only the environment but also the mind and brain itself. We call the framework computational rationality to emphasize the incorporation of computational mechanism into the definition of rational action. Theories are specified as optimal program problems , defined by an adaptation environment, a bounded machine, and a utility function. Such theories yield different classes of explanation, depending on the extent to which they emphasize adaptation to bounds, and adaptation to some ecology that differs from the immediate local environment. We illustrate this variation with examples from three domains: visual attention in a linguistic task, manual response ordering, and reasoning. We explore the relation of this framework to existing “levels” approaches to explanation, and to other optimality‐based modeling approaches.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/106911/1/tops12086.pd

Bounded Rationality and Heuristics in Humans and in Artificial Cognitive Systems

In this paper I will present an analysis of the impact that the notion of “bounded rationality”, introduced by Herbert Simon in his book “Administrative Behavior”, produced in the field of Artificial Intelligence (AI). In particular, by focusing on the field of Automated Decision Making (ADM), I will show how the introduction of the cognitive dimension into the study of choice of a rational (natural) agent, indirectly determined - in the AI field - the development of a line of research aiming at the realisation of artificial systems whose decisions are based on the adoption of powerful shortcut strategies (known as heuristics) based on “satisficing” - i.e. non optimal - solutions to problem solving. I will show how the “heuristic approach” to problem solving allowed, in AI, to face problems of combinatorial complexity in real-life situations and still represents an important strategy for the design and implementation of intelligent systems

Intonation and discourse : biased questions

This paper surveys a range of constructions in which prosody affects discourse function and discourse structure.We discuss English tag questions, negative polar questions, and what we call “focus” questions. We postulate that these question types are complex speech acts and outline an analysis in Segmented Discourse Representation Theory (SDRT) to account for the interactions between prosody and discourse

Cognitive Semantics: An Extension of the Cartesian Legacy

The basic intention of this article is to show how the cognitive semantics inherits its ancestry from the Cartesian foundation. The emergence of the cognitive semantics is envisaged here as an integral part of the knowledge evolution, in terms of shifts, which ultimately determines the future direction of our epistemological quest. Basically two questions have been emphasized here: (a) how (and what amount of) common sense metaphysics can be incorporated within the existing system of knowledge; and (b) is there any substratum where the mind-body dualism can be boiled down

ECONOMIC AGENCY THROUGH MODULARITY THEORY

Economic agency as a matter of rational decision-making and as a problem of bounded rationality has never gone too far from its earlier formalization in the 1950s. Not that the advancement on this topic is so slow, but the same problem concerning higher level cognition as another general program of cognitive science is not as easy as behavioral studies. This paper will show a parallelism between economic agency and folkpsychological perspective, and in turn will give a short description on how folk psychology is unseparable from modularity theory. In short, then there must be a way to cope with cognition as the black box of economics if we can identify the appropriate level of description of cognitive structure, i.e.: modularity theory.bounded rationality, folk psychology, modularity theory

Dynamic Semantics

This article focuses on foundational issues in dynamic and static semantics, specifically on what is conceptually at stake between the dynamic framework and the truth-conditional framework, and consequently what kinds of evidence support each framework. The article examines two questions. First, it explores the consequences of taking the proposition as central semantic notion as characteristic of static semantics, and argues that this is not as limiting in accounting for discourse dynamics as many think. Specifically, it explores what it means for a static semantics to incorporate the notion of context change potential in a dynamic pragmatics and denies that this conception of static semantics requires that all updates to the context be eliminative and distributive. Second, it argues that the central difference between the two frameworks is whether semantics or pragmatics accounts for dynamics, and explores what this means for the oft-heard claim that dynamic semantics blurs the semantics/pragmatics distinction

The Bayesian boom: good thing or bad?

A series of high-profile critiques of Bayesian models of cognition have recently sparked controversy. These critiques question the contribution of rational, normative considerations in the study of cognition. The present article takes central claims from these critiques and evaluates them in light of specific models. Closer consideration of actual examples of Bayesian treatments of different cognitive phenomena allows one to defuse these critiques showing that they cannot be sustained across the diversity of applications of the Bayesian framework for cognitive modeling. More generally, there is nothing in the Bayesian framework that would inherently give rise to the deficits that these critiques perceive, suggesting they have been framed at the wrong level of generality. At the same time, the examples are used to demonstrate the different ways in which consideration of rationality uniquely benefits both theory and practice in the study of cognition