In this talk I present the main results from Anta (2021), namely, that the theoretical division between Boltzmannian and Gibbsian statistical mechanics should be understood as a separation in the epistemic capabilities of this physical discipline. In particular, while from the Boltzmannian framework one can generate powerful explanations of thermal processes by appealing to their microdynamics, from the Gibbsian framework one can predict observable values in a computationally effective way. Finally, I argue that this statistical mechanical schism contradicts the Hempelian (...) (1958) thesis that the predictive power of a scientific theory is directly proportional to its explanatory potential, and vice versa. (shrink)

A “conceptual spaces” approach is used to formalize Aristotle’s main intuitions about time and change, and other ideas about temporal points of view. That approach has been used in earlier studies about points of view. Properties of entities are represented by locations in multidimensional conceptual spaces; and concepts of entities are identified with subsets or regions of conceptual spaces. The dimensions of the spaces, called “determinables”, are qualities in a very general sense. A temporal element is introduced by adding a (...) time variable to state functions that map entities into conceptual spaces. That way, states may have some permanency or stability around time instances. Following Aristotle’s intuitions, changes and events will not be necessarily instant phenomena, instead they could be processual and interval dependent. Change is defined relatively to the interval during which the change is taking place. Time intervals themselves are taken to represent points of view. To have a point of view is to look at the world as it is in the selected interval. Many important concepts are relativized to intervals, for instance change, events, identity, ontology, potentiality, etc. The definition of points of view as intervals allows to compare points of view in relation to all these concepts. The conceptual space approach has an immediate semantic and structural character, but it is tempting to develop also logics to describe them. A formal language is introduced to show how this could be done. (shrink)

Concepts are the building blocks of higher-order cognition and consciousness. Building on Conceptual Spaces Theory (CST) and proceeding from the assumption that concepts are inherently dynamic, this paper provides historical context to and significantly elaborates the previously offered Iterative Subdivision Model (ISDM) with the goal of pushing it toward empirical testability. The paper describes how agents in continuous interaction with their environment adopt an intentional orientation, estimate the utility of the concept(s) applicable to action in the current context, engage in (...) practical action, and adopt any new concepts that emerge: a largely pre-intellectual cycle that repeats essentially without interruption over the conceptual agent’s lifetime. This paper elaborates utility optimization by establishing three constraints on concept formation/evaluation – non-redundancy, distinctiveness, and proportionality – embedding them in a quasi-mathematical model intended for development into a formal logic. The notion of a distinctor – a quality dimension of the conceptual space in focus at any given time, used for making what we call a difference distinction – is key. The primary contribution of the revised ISDM is the way it relates concepts to action via utility optimization/actualization and the way it describes the emergence of quality dimensions through trial-by-action (trial and error), something previous presentations of CST have failed to address. (shrink)