CHR(PRISM)-based Probabilistic Logic Learning

PRISM is an extension of Prolog with probabilistic predicates and built-in support for expectation-maximization learning. Constraint Handling Rules (CHR) is a high-level programming language based on multi-headed multiset rewrite rules. In this paper, we introduce a new probabilistic logic formalism, called CHRiSM, based on a combination of CHR and PRISM. It can be used for high-level rapid prototyping of complex statistical models by means of "chance rules". The underlying PRISM system can then be used for several probabilistic inference tasks, including probability computation and parameter learning. We define the CHRiSM language in terms of syntax and operational semantics, and illustrate it with examples. We define the notion of ambiguous programs and define a distribution semantics for unambiguous programs. Next, we describe an implementation of CHRiSM, based on CHR(PRISM). We discuss the relation between CHRiSM and other probabilistic logic programming languages, in particular PCHR. Finally we identify potential application domains

Transmission protocols for instruction streams

Threads as considered in thread algebra model behaviours to be controlled by some execution environment: upon each action performed by a thread, a reply from its execution environment -- which takes the action as an instruction to be processed -- determines how the thread proceeds. In this paper, we are concerned with the case where the execution environment is remote: we describe and analyse some transmission protocols for passing instructions from a thread to a remote execution environment.Comment: 13 page

Logical Algorithms meets CHR: A meta-complexity result for Constraint Handling Rules with rule priorities

This paper investigates the relationship between the Logical Algorithms language (LA) of Ganzinger and McAllester and Constraint Handling Rules (CHR). We present a translation schema from LA to CHR-rp: CHR with rule priorities, and show that the meta-complexity theorem for LA can be applied to a subset of CHR-rp via inverse translation. Inspired by the high-level implementation proposal for Logical Algorithm by Ganzinger and McAllester and based on a new scheduling algorithm, we propose an alternative implementation for CHR-rp that gives strong complexity guarantees and results in a new and accurate meta-complexity theorem for CHR-rp. It is furthermore shown that the translation from Logical Algorithms to CHR-rp combined with the new CHR-rp implementation, satisfies the required complexity for the Logical Algorithms meta-complexity result to hold.Comment: To appear in Theory and Practice of Logic Programming (TPLP

CHR Grammars

A grammar formalism based upon CHR is proposed analogously to the way Definite Clause Grammars are defined and implemented on top of Prolog. These grammars execute as robust bottom-up parsers with an inherent treatment of ambiguity and a high flexibility to model various linguistic phenomena. The formalism extends previous logic programming based grammars with a form of context-sensitive rules and the possibility to include extra-grammatical hypotheses in both head and body of grammar rules. Among the applications are straightforward implementations of Assumption Grammars and abduction under integrity constraints for language analysis. CHR grammars appear as a powerful tool for specification and implementation of language processors and may be proposed as a new standard for bottom-up grammars in logic programming. To appear in Theory and Practice of Logic Programming (TPLP), 2005Comment: 36 pp. To appear in TPLP, 200