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An equational axiomatisation of probability functions for one-dimensional event spaces in the language of signed meadows is expanded with conditional values. Conditional values constitute a so-called signed vector meadow. In the presence of a probability function, equational axioms are provided for expected value, variance, covariance, and correlation squared, each defined for conditional values. Finite support summation is introduced as a binding operator on meadows which simplifies formulating requirements on probability mass functions with finite support. Conditional values are related to probability mass functions and to random variables. The definitions are reconsidered in a finite dimensional setting.
A wide range of intuitionistic type theories may be presented as equational theories within a logical framework. This method was formulated by Per Martin-L{o}f in the mid-1980s and further developed by Uemura, who used it to prove an initiality resul
We study the computational complexity of satisfiability problems for classes of simple finite height (ortho)complemented modular lattices $L$. For single finite $L$, these problems are shown tobe $mc{NP}$-complete; for $L$ of height at least $3$, equ
A desirable goal for autonomous agents is to be able to coordinate on the fly with previously unknown teammates. Known as ad hoc teamwork, enabling such a capability has been receiving increasing attention in the research community. One of the centra
An operator set is functionally incomplete if it can not represent the full set $lbrace eg,vee,wedge,rightarrow,leftrightarrowrbrace$. The verification for the functional incompleteness highly relies on constructive proofs. The judgement with a larg
We obtain an asymptotic representation formula for harmonic functions with respect to a linear anisotropic nonlocal operator. Furthermore we get a Bourgain-Brezis-Mironescu type limit formula for a related class of anisotropic nonlocal norms.