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20112017
most citedDecision-Theoretic Planning with non-Markovian Rewards

70 citations · 85 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LO2017

Scavenger 0.1: A Theorem Prover Based on Conflict Resolution

Daniyar Itegulov, John Slaney, Bruno Woltzenlogel Paleo

This paper introduces Scavenger, the first theorem prover for pure first-order logic without equality based on the new conflict resolution calculus. Conflict resolution has a restr…

cs.LO2016

Conflict Resolution: a First-Order Resolution Calculus with Decision Literals and Conflict-Driven Clause Learning

John Slaney, Bruno Woltzenlogel Paleo

This paper defines the (first-order) conflict resolution calculus: an extension of the resolution calculus inspired by techniques used in modern SAT-solvers. The resolution inferen…

cs.CY2015★ 1 cited

Logic considered fun

John Slaney

This report describes the development and use of an online teaching tool giving students exercises in logical modelling, or \emph{formalisation} as it is called in the older litera…

cs.AI2012★ 14 cited

Anytime State-Based Solution Methods for Decision Processes with non-Markovian Rewards

Sylvie Thiebaux, Froduald Kabanza, John Slanley

A popular approach to solving a decision process with non-Markovian rewards (NMRDP) is to exploit a compact representation of the reward function to automatically translate the NMR…

cs.AI2011★ 70 cited

Decision-Theoretic Planning with non-Markovian Rewards

C. Gretton, F. Kabanza, D. Price +2

A decision process in which rewards depend on history rather than merely on the current state is called a decision process with non-Markovian rewards (NMRDP). In decision-theoretic…