We address the problem of observables in generally invariant spacetime theories such as Einstein’s general relativity. Using the refined notion of an event as a “point-coincidence” between scalar fields that completely characterise a spacetime model, we propose a generalisation of the relational local observables that does not require the existence of four everywhere invertible scalar fields. T...

It is shown that a category-theoretic definition of chaotic system applies not only to the Smale horseshoe, a prototypical example, but also to Conway’s “Life.” Symbolic dynamics of the “Dining Philosophers” relational system is computed. A category composed of stochastic matrices is defined and its elementary properties are studied. A categorical variant of symbolic dynamics is applied to a fi...

Abstract Hoare-style program logics are a popular and effective technique for software verification. Relational an instance of this approach that enables reasoning about relationships between the execution two or more programs. Existing relational have focused on verifying all runs collection programs do not violate specified behavior. Several important properties, including refinement noninter...

The geo-spatial database is a new technology in database systems which allow storing, retrieving and maintaining the spatial data. In this paper, we seek to design and implement a geo-spatial database for managing the traveler’s demand with the aid of open-source tools and object-relational database package. The building of geo-spatial database starts with the design of data model in terms of c...

Most theories of categorization posit feature-based representations. Markman and Stilwell (2001) argued that many natural categories name roles in relational systems and therefore they are role-governed categories. There is little extant empirical evidence to support the existence of role-governed categories. Three experiments examine predictions for ways that role-governed categories should di...

Robots deployed to assist humans in complex, dynamic domains need the ability to represent, reason with, and learn from, different descriptions of incomplete domain knowledge and uncertainty. This paper presents an architecture that integrates declarative programming and relational reinforcement learning to support cumulative and interactive discovery of previously unknown axioms governing doma...