In this paper, we propose a variant of stable model semantics fordisjunctive logic programming and deductive databases. Thesemantics, called minimal founded, generalizesstable model semantics for normal (i.e. non-disjunctive) programs,but differs from disjunctive stable model semantics (the extensionof stable model semantics for disjunctive programs). Compared withdisjunctive stable model semantics, minimal founded semantics seemsto be more intuitive, it gives meaning to programs which aremeaningless under stable model semantics and is no harder tocompute. More specifically, minimal founded semantics differs fromstable model semantics only for disjunctive programs havingconstraint rules or rules working as constraints. We study theexpressive power of the semantics, and show that for generaldisjunctive datalog programs it has the same power as disjunctivestable model semantics.

How to extract negative information from programs is an importantissue in logic programming. Here we address the problem forfunctional logic programs, from a proof-theoretic perspective. Thestarting point of our work is CRWL (Constructorbased ReWriting Logic), a well established theoretical framework forfunctional logic programming, whose fundamental notion is that ofnon-strict non-deterministic function. We present a proof calculus,CRWLF, which is able to deduce negativeinformation from CRWL-programs. In particular,CRWLF is able to prove ‘finite’ failure ofreduction within CRWL.

$\lambda$Prolog is knownto be well-suited for expressing and implementing logics andinference systems. We show that lemmas and definitions in suchlogics can be implemented with a great economy of expression. Weencode a higher-order logic using an encoding that maps both termsand types of the object logic (higher-order logic) to terms of themetalanguage ($\lambda$Prolog). We discuss both the Terzo andTeyjus implementations of $\lambda$Prolog. We also encode the same logicin Twelf and compare the features of these two metalanguages for ourpurposes.

We study algorithms for computing stable models of logic programs andderive estimates on their worst-case performance that areasymptotically better than the trivial bound of $O(m 2^n)$, where $m$ is the size of an input programand $n$ is the numberof its atoms. For instance, for programs whose clauses consist of atmost two literals (counting the head) we design an algorithm tocompute stable models that works in time $O(m\times 1.44225^n)$. We present similarresults for several broader classes of programs. Finally, we studythe applicability of the techniques developed in the paper to theanalysis of the performance of smodels.

The so called “cogen approach” to programspecialisation, writing a compiler generator instead of aspecialiser, has been used with considerable success in partialevaluation of both functional and imperative languages. This paperdemonstrates that the cogen approach is alsoapplicable to the specialisation of logic programs (called partialdeduction) and leads to effective specialisers. Moreover, using goodbinding-time annotations, the speed-ups of the specialised programsare comparable to the speed-ups obtained with online specialisers.The paper first develops a generic approach to offline partialdeduction and then a specific offline partial deduction method,leading to the offline system LIX for pure logic programs.While this is a usable specialiser by itself, it is used to developthe cogen system LOGEN. Given a program, aspecification of what inputs will be static, and an annotationspecifying which calls should be unfolded, LOGEN generatesa specialised specialiser for the program at hand. Running thisspecialiser with particular values for the static inputs results inthe specialised program. While this requires two steps instead ofone, the efficiency of the specialisation process is improved insituations where the same program is specialised multiple times. Thepaper also presents and evaluates an automatic binding-time analysisthat is able to derive the annotations. While the derivedannotations are still suboptimal compared to hand-crafted ones, theyenable non-expert users to use the LOGEN system in a fullyautomated way. Finally, LOGEN is extended so as to directlysupport a large part of Prolog's declarative and non-declarativefeatures and so as to be able to perform so called mixlinespecialisations.

The work reported here introduces Defeasible Logic Programming(DeLP), a formalism that combines results of Logic Programming andDefeasible Argumentation. DeLP provides the possibility ofrepresenting information in the form of weak rulesin a declarative manner, and a defeasible argumentation inferencemechanism for warranting the entailed conclusions. In DeLP anargumentation formalism will be used for deciding betweencontradictory goals. Queries will be supported by arguments thatcould be defeated by other arguments. A query $q$ will succeed when there is anargument ${\mathcal A}$for $q$ that iswarranted, i.e. the argument ${\mathcalA}$ that supports $q$ is found undefeated by a warrant procedurethat implements a dialectical analysis. The defeasible argumentationbasis of DeLP allows to build applications that deal with incompleteand contradictory information in dynamic domains. Thus, theresulting approach is suitable for representing agent's knowledgeand for providing an argumentation based reasoning mechanism toagents.

In this paper, the optimum design of parallel kinematic toolheads is implemented using genetic algorithms with the consideration of the global stiffness and workspace volume of the toolheads. First, a complete kinetostatic model is developed which includes three types of compliance, namely, actuator compliance, leg bending compliance and leg axial compliance. Second, based on this model, two kinetostatic performance indices are introduced to provide a new means of measuring compliance over the workspace. These two kinetostatic performance indices are the mean value and the standard deviation of the trace of the generalized compliance matrix. The mean value represents the average compliance of the Parallel Kinematic Machines over the workspace, while the standard deviation indicates the compliance fluctuation relative to the mean value. Third, design optimization is implemented for global stiffness and working volume based on kinetostatic performance indices. Additionally, some compliance comparisons between Tripod toolhead and other two principal Tripod-based Parallel Kinematic Machines are conducted.

The purpose of the present study is to assess the effect of an auxiliary lateral image and display devices on manipulation performance in a virtual reality-based hand rehabilitation system. The system consists of a personal computer, a tracker, a data glove, and a display device. For this study, a projector, a monitor, and a head-mounted display were respectively used as the display devices to present three-dimensional virtual environments. Twelve volunteers were recruited to take a pick-and-place procedure at different levels of difficulty. Task time and collision frequency were the parameters used to evaluate the manipulation performance. It was found that the presence of an auxiliary lateral image was a significant factor only for the performance of the projector group and the monitor group. In addition, no statistically significant difference was found in the comparison between the projector group and the monitor group.

ADVANCES IN BlOROBOTIC VlSlON

The Australian National University Biorobotic Vision Group has described its innovative researches and developments in the field of robotic vision. The group has been researching the principles by which insects see, control flights and navigate, in order to transfer their findings to their work in robotic vision. They believe this work will help them in their aim to devise algorithms for machine vision and autonomous, visually guided robots. In particular, this work is in reference to using optic flow to measure image motion.

The researchers have already successfully developed a hover controller that can hover over an arbitary set of landmarks with no manual intervention.They have also designed an autonomous helicopter that will hover and fly without using GPS.

This paper deals with an optimum synthesis of planar parallel manipulators using two constrained optimisation procedures based on the minimization of: (i) the overall deviation of the condition number of manipulator Jacobian matrix from the ideal/isotropic condition number, and (ii) bearing forces throughout the manipulator workspace for force balancing. A revolute jointed planar parallel manipulator is used as an example to demonstrate the methodology. The parameters describing the manipulator geometry are obtained from the first optimisation procedure, and subsequently, the mass distribution parameters of the manipulator are determined from the second optimisation procedure based on force balancing. Optimisation results indicate that the proposed optimisation approach is systematic, versatile and easy to implement for the optimum synthesis of the parallel manipulator and other kinematic chains. This work contributes to previously published work from the point of view of being a systematic approach to the optimum synthesis of parallel manipulators, which is currently lacking in the literature.

This paper presents two frontal plane algorithms for 3D dynamic bipedal walking. One of which is based on the notion of symmetry and the other uses reinforcement learning algorithm to learn the lateral foot placement. The algorithms are combined with a sagittal plane algorithm and successfully applied to a simulated 3D bipedal robot to achieve level ground walking. The simulation results showed that the choice of the local control law for the stance-ankle roll joint could significantly affect the performance of the frontal plane algorithms.